Browse Topic: Hybrid electric vehicles

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Life Cycle Assessment of Greenhouse Gas Emissions from a Plug-in Hybrid Electric Vehicle with Different Powertrain Configurations in Europe2026-24-00199/21/2026
Plug in hybrid electric vehicles play an important role in transportation decarbonization. Compared with battery electric vehicles, plug in hybrid electric vehicles generally have a lower production carbon footprint due to their smaller batteries, which require far less raw material. Despite their smaller capacity, these batteries are typically sufficient to cover most daily travel distances in pure electric mode. The hybrid powertrain can be configured in multiple ways depending on the number and position of electric machines within the driveline. These configuration differences significantly influence both the total carbon footprint and the use phase greenhouse gas emissions. In this study, we evaluate the life cycle greenhouse gas emissions of a plug-in hybrid electric vehicle with various powertrain configurations in the European context. All configurations share the same premium mid-size sport utility vehicle glider. Battery capacity ranges from 20 kWh to 45 kWh, enabling an electric range of over 200 km under the Worldwide Harmonized Light Vehicles Test Cycle. The number of electric machines varies from one, as in the P2 configuration, to three, as in the P1+P3+P4 configuration. Use phase emissions for each configuration were estimated in accordance with the latest European Union emission legislation. The P2 powertrain exhibited the lowest weighted fuel and electricity consumption, whereas the P1+P3+P4 layout demonstrated the highest overall electric and fuel consumption. A sensitivity analysis of use phase emissions was performed, followed by projections for scenarios with increased renewable energy shares in both electricity generation and liquid fuel production. Finally, an extreme scenario assuming 100 % renewable electricity and fuel was analyzed.
Nguyen, Duc-Khanh, Andersson, Simon, Kristoffersson, Annika
Simulation-Based Development and Evaluation of Heat-Quantity-Based Thermal Operating Strategies for Automotive Applications2026-24-00129/21/2026
Thermal management of hybrid electric vehicle (HEV) powertrains requires the simultaneous conditioning of multiple components operating at fundamentally different temperature levels. For thermal management systems, which directly couple the thermal circuits of the internal combustion engine (ICE), electric motor and inverter (EMINV), and traction battery (BAT) for example via controllable three-way valves and a ring-circuit, the decision of when and which components to couple has a direct impact on overall powertrain efficiency. Existing thermal operating strategies rely on empirically defined temperature thresholds and fixed component priority rankings, without quantifying the actual efficiency benefit associated with each coupling decision. This paper presents the development and simulation-based evaluation of a heat-quantity-based thermal operating strategy for a prototype HEV at TU Darmstadt. The strategy introduces three new computational modules — a Q-Indicator quantifying the thermal surplus or deficit of each component, an η-Indicator evaluating real-time component efficiencies as a function of temperature and operating point, and a Δη module computing the combined efficiency gain of each potential coupling pair prior to actuation. Coupling is executed only when the combined efficiency delta is positive, replacing empirical prioritization with a quantitative, efficiency-driven decision mechanism. The strategy is evaluated against an uncoupled baseline (REF-0) and a temperature-threshold-based predecessor strategy (REF-1) across a representative commuter cycle at ambient temperatures of −10 °C, 0 °C, and +30 °C using a co-simulation environment comprising a 1D ring-circuit fluid model in AVL Cruise M and a backward-facing 0D drivetrain model in MATLAB/Simulink. The results demonstrate measurable improvements in battery preconditioning and system efficiency at cold and moderate ambient temperatures. The heat-quantity-based strategy achieves comparable or superior thermal outcomes to the threshold-based approach while activating ring-circuit coupling more selectively. At warm ambient conditions, the strategy correctly withholds intervention based on a negative efficiency delta evaluation, confirming robust scenario-adaptive behavior. The findings highlight the potential of efficiency-driven coupling logic as a generalized and physically grounded basis for thermal operating strategy development in electrified powertrains.
Stenger, Erik, Fiore, Luis, Weimer, Niko, Beidl, Christian
Comparing the Economic Performance of Series-Parallel and Range-Extended Hybrid Vehicles2026-99-15699/11/2026
This study conducted a comprehensive economic evaluation of two major HEV architectures: the series-parallel configuration and the range-extended configuration. An analysis of these two configurations was performed using integrated vehicle and control models, allowing for a direct comparison of energy efficiency and operational economy. Findings show that the range-extended configuration has clear advantages in structural complexity, simplicity of control strategy, and development cost, while its energy consumption performance is similar to that of the series-parallel configuration. The results challenge the long-standing notion that range-extended configuration is less efficient, offering a new perspective on the design and configuration choices for hybrid electric vehicles.
Li, Ping, Guo, Wencui, Nie, Guole, Niu, Yazhuo, Bai, Bateer
Recommended Practice of a Common Set of Tests for Sodium-Ion Battery Cells for the Propulsion of Battery Electric Road VehiclesJ3335_202609 (Current)9/9/2026
This document provides a recommended test guideline for secondary sodium-ion cells used for propulsion of electric vehicles including battery electric vehicles (BEV), hybrid electric vehicles (HEV), and other similar propulsion applications (e.g., forklift trucks). The objective of this document is to define common test procedures covering electrical performance, mechanical safety performance, thermal safety performance, and electrical safety performance. The results of these procedures can be used for comparative purposes. Requirements for pass/fail criteria are not defined in this document but are to be defined by the users of the document.
Battery Standards Testing Committee
Objective Quantification of Harmonic Impulsive Sounds and Interval Prediction of Sound Quality in Hybrid Vehicle Engines10-11-01-00038/28/2026
Steady advancement is observed in global research on eco-friendly and sustainable transportation. Rapid technological evolution of hybrid electric vehicles (HEVs) is documented. Lower overall noise output and more compact structures are achieved in HEV engines relative to conventional internal combustion engines. The perceptibility of harmonic impulsive sounds is significantly enhanced by these design characteristics. A close correlation is observed between these acoustic phenomena and negative human auditory perceptions. These events are treated as a core focus for HEV noise, vibration, and harshness optimization. Accurate quantification of harmonic impulsive sounds is not achieved by conventional objective indicators. A favorable balance between reliability and accuracy is not established by existing subjective prediction models. Practical engineering applications of these methods are severely restricted. A novel objective quantification method for harmonic impulsive sounds is proposed in this study. The method is established based on time–frequency masking theory and tonal strength. Bench tests in a semi-anechoic chamber and subjective evaluation experiments with standardized rating scales are performed for data collection. Collected sound signals are decomposed through an integrated approach of wavelet transform and variational mode decomposition. Targeted feature extraction is completed for harmonic impulsive sounds. A quantitative index incorporating human auditory temporal and frequency masking effects is developed. The proposed index exhibits a significantly stronger correlation with subjective evaluation results than traditional objective metrics, confirming its superior ability to reflect actual perceived sound quality. An interval prediction model for sound quality evaluation is established based on support vector machines and kernel density estimation. Traditional objective metrics and the proposed index are introduced as key input parameters. Effective and reliable prediction of HEV engine noise subjective satisfaction is achieved by the model.
Lin, Xu, Liang, Xingyu, Shi, Zhiyuan
Carbon Footprint Methodologies for Light-Duty VehiclesJ3341_202608 (Current)8/24/2026
This Disclosure Addendum will provide recommended disclosures and a standardized scenario for life cycle assessment (LCA) studies which: Include the midpoint impact category, climate change, via the impact indicator, global warming potential over a 100-year time frame (GWP100), hereby referred to as greenhouse gas (GHG) emissions Adhere to ISO 14040 and ISO14044 standards Follow the cut-off approach for allocation per ISO14067:2018 Are conducted for light-duty vehicles (LDVs) with the following powertrains: Internal Combustion Engine Hybrid Electric Plug-in Hybrid Electric and Extended-Range Electric Battery Electric These types of studies may also be referred to as a carbon footprint study or automotive LCA (A-LCA).
Hybrid - EV Committee
Research on Energy Consumption Optimization Control Strategy for Hybrid Electric Passenger Vehicles2026-01-50508/6/2026
The energy management strategy of hybrid electric vehicles (HEVs) is critical to achieving overall vehicle efficiency. Current global optimization methods involve significant computational complexity. Conventional or adaptive equivalent consumption minimization strategy (ECMS) also presents challenges in robustness and calibration efficiency, as it typically depends on real-time driving condition recognition and online parameter adjustment. To address these issues, this study proposes an engineering optimization framework based on a system efficiency lookup table approach. This method uses offline iterative simulation to determine a globally representative equivalent factor. It pre-computes optimal system efficiency, drive modes, and energy allocation across the entire operating range. These results are stored in a lookup table that the vehicle control unit (VCU) can access in real time. This approach eliminates the uncertainties associated with online optimization. It also provides calibration engineers with a quantitative tool to directly balance competing objectives, such as fuel economy and NVH. The optimized strategy increases the proportion of electric and parallel mode operation. This concentrates engine operating points within the high-efficiency zone and significantly reduces losses from multi-stage energy conversion. Simulations, dynamometer tests, and real-world road tests confirm the strategy’s effectiveness and repeatability. The approach achieves a fuel consumption reduction of approximately 0.2 L/100 km, with all test coefficients of variation (CV) remaining below 5%. The framework demonstrates good extensibility and can be adapted to different architectures, such as plug-in hybrid electric vehicles (PHEVs) and fuel cell vehicles (FCVs). It offers a universal and efficient engineering solution for optimizing energy consumption in hybrid powertrain systems.
Lin, Haoqiang, Wang, Jinhang, Chen, Lihua, Li, Huan
Research on Reliability Test Methods for Electric Drive Axle Differentials2026-01-50447/31/2026
With the rapid development of the global economy, issues such as the energy crisis and environmental pollution have become increasingly severe. Owing to their environmental friendliness, structural simplicity, and high energy efficiency, electric vehicles have attracted widespread attention. Electric drive technology serves as the most promising and versatile propulsion solution for battery electric vehicles, hybrid electric vehicles, and fuel cell vehicles. As an advanced mechatronic transmission system, the electric drive axle offers high transmission efficiency, flexible packaging, and ease of digital and active chassis control integration, and has thus been increasingly adopted in modern vehicle architectures. The differential is a key component within the electric drive axle, responsible for regulating the rotational speed difference between the left and right wheels and ensuring balanced torque distribution. It plays a decisive role in vehicle stability and traction performance. This study focuses on the reliability testing methodology for differentials in electric drive axles, primarily including the extraction of reliability test conditions and the feasibility analysis of the proposed testing scheme. Specifically, based on the parameters of a given electric vehicle, a Simulink model of the motor and differential is established, and a complete four-wheel-drive vehicle model is constructed. Through simulation under typical driving conditions, operational data of the rear-drive axle differential are obtained. The collected data are then preprocessed and subjected to dimensionality reduction using Principal Component Analysis. The selected principal components are further analyzed using K-means clustering to construct representative differential reliability test conditions. The limitations of existing testing methods are analyzed based on the simulated results and relevant literature. Finally, a reinforced fatigue testing method for the differential is designed according to the extracted test conditions, and the feasibility of the corresponding test bench is evaluated.
Zheng, Hongyu, Li, Ziyu, Wang, Dajiang, Tian, Kai
Collapse Strength and Crush Space Analysis in Lateral Side Pole Impact of an Electric Vehicle2026-01-50527/31/2026
High-Voltage Battery (HVB) protection in lateral pole impact is very important due to severe nature of the impact. Unlike frontal impacts, vehicles have limited range of space and capacity to absorb kinetic energy in lateral side impacts. Nowadays, computer-aided engineering (CAE) using finite element analysis (FEA) is utilized routinely to simulate high-speed crash events of varied type, including side pole impact. These CAE applications focus on the analysis and design of HVB when the vehicle structure is well-developed. CAE methods are time-consuming and are not suited during the pre-program stage when the structure is only in a concept stage and not even a reasonable CAD is available/developed in any sense to use these methods. There is no analytical tool available to understand how to define the characteristics of the structure that surrounds and protects the HVB. The primary motive of this publication is to help with this aspect of vehicle planning/development. Needless to state that this procedure can also be used in planning/developing of internal combustion engine (ICE) and hybrid vehicles, as well. The objective therefore is to develop a simple method/procedure that can give reasonably accurate estimation of the collapse/crush force required for a specified crush space and hence protect the critical components, such as HVB and fuel tank. This analytical method also gives some insight into the optimal use of the upper body (rocker and floor cross-members) and underbody (ladder frame) parts. It was found, for a problem under consideration, optimum kinetic energy to be absorbed by the upper body is 32.5% to avoid intrusion into HVB.
Alavandi, Bhimaraddi, Midoun, Djamal, Frank, Randy
Model-Based Optimization and Evaluation of Hybrid Powertrains for Commercial Heavy-Duty Class 8 Truck Applications02-19-04-00257/27/2026
In an ever-evolving landscape of emission regulations, charging infrastructure, customer demands, fuel/energy costs and decarbonization goals, heavy-duty on-road vehicle manufacturers continue to evaluate alternative powertrain technologies. While most heavy-duty vehicle manufacturers now have battery electric vehicles (BEVs) in their portfolio, significant challenges of charging infrastructure, range anxiety, payload capacity reduction and upfront costs have contributed to their lower adoption rates. Plug-in hybrid electric vehicles (PHEVs) have significant potential of leveraging upcoming BEV infrastructure and component supply chains to reduce operating costs while still maintaining longer range and payload capacity benefits of conventional ICE powertrains. This article applies a model-based approach to evaluate multiple Class 7–8 heavy-duty powertrain configurations. A system-level (1D) model of the conventional diesel ICE-based truck was developed in GT-Suite and validated against on-road test data. Using the diesel ICE model as a baseline, system-level models for different hybrid configurations were adapted, and their powertrain architecture was optimized at the system level. Additionally, an equivalent consumption minimization strategy (ECMS) for energy management was also optimized for each of the hybrid powertrain configurations to maximize fuel efficiency and emission benefits. All the hybrid configurations were then compared against the conventional diesel ICE Class 8 truck in terms of performance (acceleration, top speed, gradeability and startability), fuel economy (real-world cycles and certification cycles), emissions, and range for long-haul applications. Unique to this approach is the simultaneous co-optimization of powertrain component sizing and supervisory control logic by utilizing a Genetic Algorithm–based optimization approach. Results indicate that all parallel hybrid architectures (P2, P2–P3, and P4) achieve performance (acceleration, top speed, gradeability, and startability) parity or improvement compared to baseline diesel architecture. P2-based architectures demonstrated a 12–14% improvement in fuel economy on representative real-world cycles when operating in a blended charge-depleting–charge-sustaining mode of operation, and a 4–6% improvement in fuel economy when operating in charge-sustaining mode alone. By quantifying these results across diverse topologies, this work addresses a significant research gap in the holistic evaluation of Class 8 hybrids, specifically, the trade-off between multi-speed electric drives, system-level mass increases, and real-world fuel economy, that remains underexplored in current literature.
Baburaj, Adithya, Paul, Sumit, Dhanraj, Fnu, Joshi, Satyum, Franke, Michael
An Updated Data-Driven Greenhouse Gas Emission Rate Analysis for Vehicle Comparisons Applied to Europe14-15-03-00167/25/2026
This study presents a data-driven lifecycle assessment (LCA) framework for evaluating greenhouse gas (GHG) emissions from passenger vehicles across European electricity systems. The analysis compares battery electric vehicles (BEVs), full hybrid electric vehicles (FHEVs), and internal combustion engine vehicles (ICEVs) using both conventional average electricity emissions factors and time-resolved marginal emissions, referred to as real charging emissions (RCE). Hourly generation and interconnector/cross-border flow data for 2023 from 29 European countries are processed to estimate consumption-based marginal emissions rates that account for grid dispatch behavior and cross-border electricity flows. The approach is applied to two vehicles where multiple powertrains are available on the same platform, the 2024 Hyundai Kona (available as a BEV, FHEV, and ICEV) and Peugeot 2008 (available as a BEV and ICEV), to isolate drivetrain-related lifecycle differences. Results show substantial divergence between average and marginal emissions estimates, with a mean absolute difference in BEV–FHEV lifecycle emissions of 31–36 g CO2 eq/km across Europe. In several countries with carbon-intensive marginal generation, including Poland and Cyprus, BEVs may exhibit higher lifecycle emissions than comparable hybrids, while low-carbon grids such as Norway, Sweden, and France provide large BEV advantages. Sensitivity analyses demonstrate the importance of transmission losses, temperature effects, electricity imports, and charging timing. These findings highlight the limitations of average grid emissions factors in vehicle LCAs and underscore the importance of geographically and temporally resolved data-driven electricity emissions when assessing electrified vehicle climate impacts.
Drew, Alfred, Burton, Tristan, Senecal, Kelly, Davy, Martin, Leach, Felix
Fuel Savings from Predictive Charge Control Based on Short-Trip Duration in Series Hybrid Electric Vehicles14-15-03-00157/10/2026
Series hybrid electric vehicles (HEVs) employ an electric motor for propulsion, while the internal combustion engine operates solely as a generator under energy-efficient speed and load conditions. Owing to this architecture, series HEVs can achieve high fuel efficiency with a relatively simple control structure. However, conventional energy management systems (EMSs) often prioritize battery state-of-charge (SOC) stabilization, which can lead to frequent engine start–stop operations and unnecessary fuel consumption, particularly in short-trip driving. This study aims to enhance energy management performance in series HEVs by optimizing engine power generation timing based on predicted short-trip duration. A computationally efficient, rule-based prediction model is developed using real-world driving data, in which short-trip duration is estimated from vehicle speed and acceleration. Due to its low computational load, the proposed model is suitable for implementation in an onboard electronic control unit (ECU). The proposed control strategy initiates engine power generation when the battery SOC is low and the predicted trip duration is long, and suppresses generation when the SOC is sufficiently high or the predicted trip is short. A detailed vehicle model incorporating an engine, generator, electric motor, inverter, and battery is developed in Modelica to evaluate the proposed strategy. Simulation results demonstrate that the proposed EMS significantly reduces the frequency of engine start–stop events, leading to fuel economy improvements of 3.6% under the WLTC (excluding the extra-high phase) and 13.4% in a real-world urban–rural driving cycle, compared with a commercialized baseline vehicle. These results confirm the effectiveness and practical applicability of the proposed EMS for passenger vehicle applications.
Mizushima, Norifumi, Sato, Akira, Kuboyama, Tatsuya, Moriyoshi, Yasuo
Review of Power Management Technology for Turbine Hybrid Electric Propulsion Systems2026-99-05317/10/2026
The turbine hybrid electric propulsion system is an important form of green aviation. Unlike the single form of aviation power scheme, the hybrid energy system is flexible in architecture, uses two or more energy forms, and has diverse energy sources. Under different mission requirements, it needs to meet the requirements of mass balance, energy balance, and power demand, etc. Therefore, The control and distribution management between different energy systems have become the key to hybrid power, and power management technology is one of the key challenges in the development of aviation hybrid power control systems. This paper reviews the current structural forms of aviation turbine hybrid electric propulsion systems, analyzes the current research status of power management technology for aviation hybrid systems, and points out that the online power management method based on optimization is the best power management technology solution for turbine hybrid electric propulsion systems. Establishing a high-precision and realtime on-board power calculation model, breaking through the power management method based on the integrated flight and engine, and improving the applicability of the power management method throughout the service life are important directions for promoting the development of online power management technology.
Cai, Changpeng, Liu, Hao, Gu, Jiangwei, Li, Shunming, Zhang, Haibo
Optimization of Preheating Energy Distribution for Low-Temperature Cold Starts in Diesel-Electric Hybrid Vehicles2026-99-05167/10/2026
To minimize energy input and preheating time, this study first analyzed the energy consumption of intake air, lubricating oil, and coolant preheating through simulations. Temperature rise data were collected under various heating parameters. Next, simulations evaluated the hybrid power system’s resistance characteristics immediately after startup and the combustion parameters during the first cycle post-ignition under different temperatures. The temperature thresholds for successful start-up were identified, defining the feasible domain for optimization. Optimization calculations aimed to minimize preheating time and energy input, constrained by maximum preheating power. Results show that intake air heating has the greatest impact on start-up success, followed by lubricating oil heating. It is recommended to increase energy allocation to intake air and lubricating oil heating. This optimized strategy reduces preheating time and energy input by approximately 26% without changing the preheating equipment.
Wei, Shengchen, Zhao, Zhenfeng
Multi-Scale Modelling of Localized Battery Degradation in Heavy-Duty Series Hybrids: From Electrochemical Impedance Spectroscopy to Powertrain and Battery Pack Performance2026-01-07477/1/2026
Hybrid electric vehicles rely heavily on battery pack power capability, which is often compromised by non-uniform aging and thermal gradients. Conventional battery models typically use bulk state-of-health metrics, failing to capture localized degradation that leads to current imbalances and reduced pack utility. This paper presents a multi-scale modelling framework that integrates Electrochemical Impedance Spectroscopy data into a fractional-order equivalent circuit model to simulate localized degradation in Lithium Iron Phosphate cells. Results show that the terminal voltage of LFP cells can be accurately modelled using the proposed fractional-order equivalent circuit with a discrete transfer-function implementation, maintaining root-mean-square errors below 20 mV across most state-of-health and state-of-charge conditions. The validated cell model is then extended to a degradation-aware battery pack representation. The battery pack in this work utilizes a 200-kWh, 800 V architecture consisting of five modules connected in parallel, each module composed of 13 parallel strings of 250 series cells, evaluated under multiple degradation scenarios. By integrating this pack model into a Class-8 series hybrid powertrain simulation, this study quantifies how cell-to-cell heterogeneity impacts vehicle performance under the VECTO regional delivery drive cycle. At the vehicle level, these battery constraints influence engine duty cycles and battery pack stress metrics. When localized degradation reaches up to 40% in one module while the remaining modules degrade up to 20% to 30%, such inhomogeneous degradation reduces the minimum pack terminal voltage by approximately 27% and increases peak discharge current by more than 30%, resulting in more rapid degradation. These battery-level limitations translate into higher fuel consumption by up to 6% in a charge-sustaining scenario.
Safavi, Seyed Reza, Homayouni, Hooman, Shoa, Tina, Wang, Jason, McTaggart-Cowan, Gordon
Synergistic Integration of Advanced Combustion and Air-Path Technologies to Maximize Internal Combustion Engines Efficiency in Hybrid Applications2026-01-07337/1/2026
This paper assesses the efficiency limits of light-duty vehicle propulsion systems based on reciprocating internal combustion engines (ICE) in the current state of the art and in the next five-year horizon, considering their combination with technologies such as electric turbocharging and hybridization, while excluding plug-in hybrid configurations so that fuel remains the primary onboard energy source. A systematic methodology is applied to evaluate the influence of key variables—heat transfer, air–fuel ratio, and compression ratio—on engine performance, integrating these variations into a simulation model to capture their interactions and effects. The resulting parametric study enables the generation of new engine maps that exploit synergies between parameters and enhance the prediction of engine behaviour across different operating conditions, forming the basis for assessing potential advancements in hybrid powertrain architectures. These maps are then used to define performance expectations for hybrid vehicles, identifying optimal parameter combinations to guide future technology development and improve efficiency in hybrid powertrain design. The proposed powertrain architectures are integrated into a representative vehicle model, considering two vehicle typologies: a compact passenger car and a sport utility vehicle (SUV). To quantify the potential fuel-consumption benefits, an intelligent energy-management algorithm is implemented to supervise and optimize system operation over a WLTC driving cycle. The results indicate that the proposed configurations can achieve fuel-consumption reductions exceeding 20%, demonstrating the effectiveness of both the powertrain designs and the control strategies. Overall, the findings highlight the significant efficiency potential of advanced ICE-based propulsion systems when combined with near-term technologies such as electric boosting and hybridization, confirming the viability of these improvements and providing a robust basis for future hybrid vehicle development focused on maximizing energy efficiency in transportation.
Pla, Benjamin, Dolz, Vicente, Serrano, Jose R., Gómez-Vilanova, Alejandro, Oliva, Fermin, Cardenas, Maria, Ariztegui, Javier
Methodology for Developing a Learning-Based Energy Management Strategy for Hybrid Electric Vehicles via Soft Actor-Critic (SAC) Deep Reinforcement Learning Algorithm2026-01-07747/1/2026
The optimization of energy management strategies for hybrid electric vehicles is crucial for minimizing fuel and electrical energy consumption while maintaining the energetic stability of the electrical system. Conventional heuristic, rule-based approaches typically rely on classical optimization techniques and manual calibration by experienced engineers. These methods often suffer from simplified assumptions, sub-optimality, and are increasingly time-consuming given the growing complexity of modern hybrid powertrain architectures. This research proposes a novel methodology for the development of a learning-based energy management strategy (EMS) via deep reinforcement learning (DRL) to transition toward highly automated, data-based, and optimization-based development approaches. The methodology utilizes the Soft Actor-Critic (SAC) algorithm, an off-policy actor-critic method, to train an agent through experiences by interacting with an environment. The environment consists of a backward-looking, quasi-static vehicle longitudinal dynamics simulation model of an exemplary P2 plug-in hybrid electric vehicle (PHEV) combined with a database of customer-representative driving profiles. The agent learns optimal control policies through defined states and actions, optimizing a multi-criteria reward function that balances fuel efficiency against energetic stability. The framework permits the definition of both non-predictive and predictive states. Additionally, a shield function is implemented to consider hard constraints ensuring safe and stable operation. Variation calculations and sensitivity analyses regarding reward function shaping and hyperparameter tuning are conducted. The agent is trained in an offline simulation environment, and the learned policy of the trained deep neural network (DNN) is transferred into deterministic control maps, applicable to vehicle control units, ensuring interpretability, reproducibility, and compliance with certification requirements. Finally, exemplary simulation results of the DRL-EMS approach are presented and compared to benchmark equivalent consumption minimization strategy (ECMS). In conclusion, the proposed methodology enables a generally valid approach for the development of learning-based energy management strategies towards close-to-optimal strategies while reducing manual calibration effort.
Metzler, Sebastian, Winke, Florian, Jungen, Mario, Schmiedler, Stefan, Hofmann, Peter, Geringer, Bernhard
NVH Design and Refinement of Dedicated Hybrid Engine on Range-Extended Electric Vehicle2026-01-06886/20/2026
Simplicity and electrification of the propulsion system are one of the most important trends in vehicle development and integration process. The complexity of NVH (Noise, Vibration and Harshness) design and refinement is the core challenge to this process. Customers’ expectations of an unnoticeable engine during driving make this challenge more critical [1]. Apart from the overall sound pressure level, the sound quality is even more important due to the lack of noise masking effects [2]. Therefore, the development team has reached an internal consensus that NVH attributes are the top priority in engine development. This paper describes the NVH development process of a dedicated hybrid engine for the range extender electric vehicle (REEV) application, beginning with an introduction to REEV system as well as the operating condition data of long-distance road tests. Based on the road test data, the engine technical specification is defined accordingly and broken down into design targets for all individual components. Subsequently the design target is finally achieved through the definition of engine architecture, hardware selection, and individual component simulation and optimization. With regard to the NVH refinement, the NVH issues such as global crankshaft vibration, start impacts, high-pressure fuel system ticking, and acoustic encapsulations studies are discussed. Finally, the appropriate optimization proposals are summarized and the bench test results are presented.
Wang, Hao, Zhang, Guiqiang
Potential of ORC-Based Waste Heat Recovery in Conventional and Hybrid Heavy-Duty Powertrains2026-37-00186/9/2026
Heavy-duty vehicles significantly contribute to greenhouse gas emissions and urban air pollution, especially during cold-starts and transients when engine and aftertreatment efficiencies drop. Waste heat recovery (WHR) via Organic Rankine Cycle (ORC) systems offers a practical solution to improve fuel efficiency and cut CO₂ in real-world heavy-duty operations. This study examines ORC-based WHR integration into conventional and hybrid powertrains of an Isuzu FTR850 truck, analyzing four configurations: Shell-and-Tube or Plate heat exchangers with simple or regenerative ORC layouts. For hybrids, it compares two engine sizes and energy management strategies: an optimized fuzzy logic approach versus constant-power operation to enhance exhaust heat recovery. A validated quasi-static simulation framework is used to predict fuel consumption and exhaust properties over representative duty cycles. 2D performance maps using exhaust temperature and mass flow as inputs are used to model the WHR under off-design conditions. Results show that the recovery of waste heat WHR depends on the hybridization level and strategy. Conventional powertrains benefit most from Shell-and-Tube exchangers, recovering ~2 kWh of electrical energy per 8-hour cycle and reducing fuel consumption by 0.5%. Hybrid setups recover up to 3.9 kWh from exhaust gases with a simple layout coupled with a Shell-and-Tube heat exchanger under constant-power control. Electricity is used to support onboard auxiliaries and battery charging, further lowering fuel demand (-44%) and emissions. Finally, a multi-objective optimization was performed to exploit the synergy between hybridization and WHR while maintaining acceptable payload and battery operating conditions.
Donateo, Teresa, Morrone, Pietropaolo
Heavy-Duty Nonroad Material Handler Electrification, Part 2: Energy Efficiency and Performance Evaluation02-19-03-00166/2/2026
Decarbonization efforts achieved through electrification in nonroad mobile machinery can realize a reduction in fuel consumption of more than 20%, thanks to concepts familiar to light-duty passenger vehicles. This case study compares the results of a hybrid-electric material handler to its conventional counterpart, utilizing machine-specific drive cycles presented in part one of this paper series. The hybrid prototype features an extended-range electric vehicle (EREV) powertrain that demonstrated substantial energy efficiency improvements. Specifically, there was a reduction in equivalent fuel consumption of 75% when operating in electric-only mode, and 33% when maintaining the battery by charging with an on-board generator. Together, the efficiency improvements can be extrapolated over a low-intensity, 8-h shift characterized by significant idle time and highly dynamic engine load for a 47% reduction in net energy consumption. Key technologies that led to this improvement included engine downsizing and decoupling, regenerative braking, and an electrohydraulic pump unit with advanced controls. This study explains details of the powertrain architecture and subsystems that were implemented on a demonstration vehicle, control strategies used to meet project goals, and an analysis of energy consumption from testing on a closed course. Also included in this study is a discourse on comparison metrics that can be used for quantifying the energy consumption differences between hybrid-electric and conventional diesel powertrains in nonroad mobile machinery.
Czarnecki, Alexander, Goodenough, Bryant, Worm, Jeremy, Robinette, Darrell, LaTendresse, Phil, Westman, John, Subert, David, Heath, Matthew, Kiefer, Dylan, Black, Andrew
Harbinger extends its range of medium-duty EVs26TOFHP06_126/1/2026
Harbinger revealed its HC Series Cab during Work Truck Week 2026 in Indianapolis, Indiana. The HC Series is a new line of medium-duty, low cab forward vehicles available as both an electric and plug-in hybrid model. Harbinger states that the HC Series' hybrid powertrain uses a range-extended hybrid platform with a gasoline engine to recharge the truck's batteries, extending range up to 500 miles (805 km), depending on upfit configuration and drive cycle.
Wolfe, Matt
EDITORIAL: Maybe more than ever, let's talk transportation diversity26AUTP06_066/1/2026
Some months, the diversity that makes up the automotive industry - and the broader transportation space - is more in-my-face than others. A series of recent conferences put this at the top of mind for me. The most recent was the International Transport Forum Summit in Leipzig, Germany, with the theme of “Funding Resilient Transport.” The name hints at the actionable kinds of discussions I heard in sessions like “Hydrogen as an Enabler of a Resilient Transport System” and a representative of a well-known Swedish packaged-furniture brand telling the room, “We do not need any more testing of pilots. We are ready to scale.”
Blanco, Sebastian
A Study on the Future of Battery Based Electric Aircraft Propulsion2026-26-07826/1/2026
Today the aviation industry is witnessing a paradigm shift in the propulsion technology which has been unseen since the 1930s, when the gas turbine took over from the more established piston engines. For the emerging electric propulsion to survive and flourish, it must demonstrate clear superiority over the mature baseline technology of the gas turbine. It is a fact that the current battery technology is a limiting factor as it is not competitive compared to a gas turbine that is 30-50 times more energy dense. Naturally, the present electric propulsion developments concentrate on smaller aircraft applications and use on a large aircraft is possibly decades away. Apart from the energy density, from a thermal perspective the architectures are vastly different from each other. A conventional aircraft fitted with a gas turbine has readily available heat sinks in fuel and air that aids in heat transfer. Compressed air bleeds from the engine manage the thermal demands of the engine itself plus the aircraft systems. On the other hand, a battery-based aircraft does not have this advantage and therefore must deploy dedicated thermal management systems for cooling and heating demands, and that drains energy from the battery. This paper summarizes a study of the Electric Propulsion Systems’ (EPS) Technology Readiness Level (TRL), a Theory of Inventive Problem Solving (TRIZ) trends of engineering system evolution, comparison with conventional aircraft/gas turbine configuration including their thermal management systems, and the impacts on type certification regulations. TRL shows hybrid-electric leads as a bridge between gas turbines and electric systems, followed by electric only propulsion due to slower battery technology breakthroughs, while distributed propulsion lags due to novel airframe and thermal challenges. TRIZ analysis suggests that integrating self-cooling, structural composite batteries, and distributed propulsion with intelligent thermal management can propel EPS to new heights. A comparison of the propulsion systems showed that the thermal management and materials selection will be the key focus areas. The regulatory authorities are adapting the airworthiness regulations to the ongoing changes, and more regulatory evolution is likely to keep up with these technological trends.
Arun, K P, Srinivas, Varsha, Joshi, Jayanth, Suresh, Chandini, Naskar, Proloy Jyoti
Design and Performance Research of an Integrated Thermal Management System for Hybrid Electric Light Trucks2026-99-07355/15/2026
Addressing issues in traditional hybrid light trucks—such as low overall energy utilization efficiency and performance degradation of key components under extreme operating conditions—this study presents a novel, high-efficiency, integrated vehicle thermal management system. By coupling various subsystems, the system achieves efficient and rational utilization of the vehicle’s overall energy consumption. Comparative simulation analyses were conducted under different ambient temperatures and initial state-of-charge (SOC) levels to verify the reliability of the designed integrated thermal management system. Results show the system can meet the temperature requirements of all components under both high and low-temperature conditions. Meanwhile, findings indicate that ambient temperature and power modes have a substantial impact on the temperature of each component, and there is potential for utilizing motor waste heat. These outcomes provide a reference for the subsequent optimization of control strategies for thermal management systems in hybrid light trucks.
Meng, Shun, Zhang, Chunyu, Zhang, Yu, Zhang, Dong, Yao, Mingyao, Qiu, Liang, Wu, Yadong, Qian, Yejian
Research on Waste Heat Recovery Characteristics of Electric Drive System in Hybrid Electric Light-Duty Trucks2026-99-07225/15/2026
Aimed at the high energy consumption for battery heating of a light hybrid truck in low-temperature winter, this paper proposes an optimized battery thermal management scheme based on motor waste heat and PTC cooperation. Then it verifies its energy-saving performance based on multi-condition simulation and testing. Taking the constant-speed condition at -5°C as an example, firstly, the accuracy of the battery thermal management model is verified by comparative simulation and test. Then, based on the verified model, the battery thermal management model is simulated under typical winter conditions at 0°C and 5°C. The analysis results show that, when the battery temperature is raised from the initial state to a certain target, the energy consumption of the motor waste heat-assisted PTC heating scheme is obviously less than that of PTC heating. The energy saving rates are 33.137% at -5°C, 32.45% at 0°C, and 32.56% at 5°C, respectively. The research results have proved that the effective utilization of motor waste heat can reduce PTC energy consumption.
Meng, Shun, Zhang, Dong, Zhang, Yu, Zhang, Chunyu, Yao, Mingyao, Qiu, Liang, Qian, Yejian
The Impact of Hybrid Electric Propulsion Technologies on Medium Lift Rotorcraft PerformanceF-0082-2026-02185/5/2026
This paper explores the potential of three different hybridization solutions for a medium-sized rotorcraft: an electric tail rotor, an "eco-mode", and a "boost-mode". The solutions were evaluated as a retrofit to a generalized medium lift rotorcraft and the impact on performance across five mission types, representative of the typical use cases for a military rotorcraft, was assessed. Two separate rotorcraft performance modelling tools were used to carry out the assessment, allowing for the results to be cross-examined. The models predicted performance gains for the eco-mode configuration when utilizing the single engine cruise capability for low-speed applications. Likewise, the models predicted improved performance for the boost-mode configuration when operating at hot and high (6,000 ft, 95°F) conditions due to the increased power provided by the battery system. However, all three solutions suffered from increased platform empty weight which negatively impacted performance at certain flight states.
Hopkins-Bain, Aaron, Vegh, Michael, Goldberg, Chana
Conceptual Design of Hybrid-Electric Propulsion System for a Light UAVF-0082-2026-01645/5/2026
The present work focuses on the sizing and analysis of a parallel hybrid propulsion architecture for a conventional rotary light Unmanned Aerial Vehicle (UAV) in the 200kg class. First, the design methodology is outlined, with an emphasis on the optimization of the battery pack, which is one of the most crucial component of the whole powertrain. The sizing approach is applied to a wide range of thermal and electric power ratios, as well as two distinct hybridization strategies, to investigate the broad design space and discover possible sweet spots. For this aim, the various design points are then evaluated in terms of impact on aircraft capabilities, considering both extensive and intensive performance. Hence, the results provide the main advantages and disadvantages, performance wise, of the hybrid propulsion in comparison to a conventional full thermal solution.
Rovera, Eugenio, Corno, Matteo, Trivella, Andrea, Bonini, Valerio, Nesci, Andrea
A Latent Space Framework for Modeling Transient Engine Emissions Using Joint Embedding Predictive Architectures2026-01-04234/7/2026
Accurately modeling and controlling vehicle exhaust emissions, particularly during highly transient events such as rapid acceleration, is crucial for meeting stringent environmental regulations and optimizing modern powertrain systems. While conventional data-driven modeling methods, such as Multilayer Perceptrons (MLPs) and Long Short-Term Memory (LSTM) networks, have improved upon earlier phenomenological or physics-based models, they often struggle to capture the complex nonlinear dynamics of emission formation. These monolithic architectures attempt to learn from all available data, which increases their sensitivity to dataset variability. They often require increasingly deep and complex architectures to improve performance, thereby limiting their practical utility. This paper introduces a novel approach that overcomes these limitations by modeling emission dynamics in a structured latent space. Using a rich dataset combining real-world driving data from a Portable Emission Measurement System (PEMS) with high-frequency hardware-in-the-loop test bench measurements, a Joint Embedding Predictive Architecture (JEPA) is leveraged. This framework learns to abstract away irrelevant information and encode only the key factors governing emission behavior into a compact, robust latent representation. The resulting model demonstrates superior data efficiency and predictive accuracy across diverse transient regimes, exhibiting stronger generalization than the high-performing LSTM baseline. Structured pruning and post-training quantization are applied to the JEPA framework to enhance the model’s suitability for real-world deployment. This combined strategy significantly reduces the model’s computational footprint, minimizing inference time and memory demand, with only a marginal impact on accuracy. This yields a highly accurate model well suited to on-board implementation of advanced control strategies, such as model predictive control or model-based reinforcement learning, in both conventional and hybrid electric powertrains. The results indicate a clear pathway toward more efficient and robust emission control systems for next-generation vehicles.
Sundaram, Ganesh, Gehra, Tobias, Ulmen, Jonas, Heubaum, Mirjan, Görges, Daniel, Günthner, Michael
BEV Incremental CO 2 Emissions in a Ranked Order Electric Grid2026-01-04244/7/2026
Battery Electric Vehicles (BEV) have been sold as ‘Zero Emissions Vehicles’ (ZEV) by governments to reduce transportation CO2. While they are not ZEV because they run on grid electricity, they could be ‘effectively ZEV’ if the incremental CO2 is ‘very small’. At the national level, this is estimated using following metrics: (1) Internal Combustion Engine Vehicle (ICEV) fuel consumption, from the total US gasoline consumption divided by the total fleet miles driven, 25 mpg or 350 g CO2/mi, (2) Strong Hybrid Electric Vehicles (HEV) about one third less, 240 g CO2/mi. (3) BEV energy consumption, using data from systematic on-road testing of a wide range of vehicles, estimated at 40 kWh/100 mi for a US sales mix. (4) Electricity marginal CO2: in a ranked order grid, zero-CO2 sources are prioritized and supplemented by fossil sources. IEA hourly data show that the US 48 contiguous states are self-contained, with zero-CO2 sources providing a third of total demand. The response to hourly demand changes comes largely from natural gas and coal power stations, with EPA data showing a combined marginal CO2 of 600 g CO2/kWh. On replacing an ICEV by a BEV, the reduction in gasoline use, - 350 g CO2/mi, is offset to two thirds by higher electricity consumption, 40 x 600 / 100 = + 240 g CO2/mi. BEV marginal CO2 is therefore similar to HEV, and not ‘much smaller’ than ICEV. This is because HEV engines and fossil power stations have similar efficiency and similar fuel CO2 intensity.
Phlips, Patrick
Establishing a Standard S-Factor: Improving Accuracy and Flexibility in SOC Corrections for HEV Testing2026-01-04224/7/2026
Hybrid-electric vehicle (HEV) fuel economy test procedures require that the net energy change (NEC) of the battery not interfere with measuring accurate fuel consumption results. SAE J1711-2010 required the NEC to stay within 1% of fuel energy consumption, assuming that residual changes in state of charge (SOC) would have negligible impact. In practice, however, the asymmetry between fuel and electricity conversion efficiencies means that an imbalance of one unit of battery energy can translate into a likely fuel consumption error of roughly three units. A standard S-Factor, a dimensionless ratio of marginal fuel change to marginal NEC change, was introduced in J1711-2023 to improve SOC correction procedures. The method improves upon the previous J1711 (2010) accuracy by correcting all results for NEC changes and expands the NEC-to-fuel ratio (NECFR) window, enabling HEVs to use electric propulsion more aggressively and potentially achieve higher fuel economy in testing and real-world usage. Using a standardized value (instead of requiring additional testing to determine the vehicle-specific value) provides a simple, low-burden approach across HEV designs. Empirical data, supported by simulations of HEV powertrains, indicate that there exists a practical range of S-Factors common to efficient HEV designs. The standard value represents a defensible best estimate within this range, close enough to provide corrected results with minimal error. The method also allows the NECFR window to be doubled (e.g., from ±1% to ±2%) while improving the fidelity of final fuel consumption results compared with the legacy procedure. This paper reviews the data and simulation work used to identify practical S-Factor values, evaluates the resulting correction accuracy across vehicle types and test cycles, and demonstrates that a single standardized S-Factor provides consistent results within an expanded NECFR window.
Duoba, Michael
A Study on Fail-Safe and Limp-Home Strategies for Electric Drive Failures in P1-P2 (P)HEVs2026-01-04274/7/2026
Hyundai Motor Company’s TMED-II hybrid system adopts a P1–P2 parallel motor layout, which improves power distribution flexibility but increases reliance on electric drive components. Failures in motors, inverters, or other power electronics can critically affect drivability and safety, making robust Fail-Safe strategies essential. This study proposes a three-stage, sequential Limp-Home strategy for P1–P2 HEVs under P2 motor system failure. Unlike conventional methods that open the main relay and rely solely on the engine, the proposed approach keeps the high-voltage (HV) system active whenever possible to maintain performance, safety, and comfort. Stage 1 – P1 motor-based State of Charge (SOC) control: Keeps the main relay closed and uses the P1 motor to maintain SOC within set limits. Overcharge is mitigated by operating the motor in discharge mode, and overdischarge is mitigated through regenerative operation. Engine torque is adjusted to match motor torque demand, preserving launch performance and gradeability. Stage 2 – Engine speed-limiting control: At higher speeds, Stage 1 alone may be insufficient to manage SOC. This stage limits engine speed (and consequently P1 motor speed as they are mechanically coupled) to suppress overcharge caused by back electromotive force (back-EMF). Coordinated control applies gearshift intervention and fuel cut to prevent rapid engine speed rises, reducing overcharge risk at the source. Stage 3 – HV Battery main relay-off mode: If overcharge or overdischarge risks remain after Stage 2, the HV system is cut off as the final safeguard. After cutoff, the P1 motor’s back-EMF powers essential loads such as HVAC, electric oil pump, and the low-voltage DC–DC converter, and the vehicle transitions to engine-only Limp-Home driving to avoid shutdown. Production-vehicle tests confirmed the stepwise, software-only strategy maintains SOC within safe limits, preserves key loads, sustains drivability, and is patented in production models.
Rho, Jeongwon, Park, Sangcheol, Oh, Sung Hwan
The Effects of Ethanol on Combustion in a Super-Lean-Burn Engine2026-01-03034/7/2026
To mitigate global warming, many countries are working toward carbon neutrality. Reducing CO₂ emissions from vehicles requires electrification technologies in hybrid and plug-in hybrid electric vehicles (HEVs, PHEVs) and improving thermal efficiency of internal combustion engines (ICEs). Lean-burn combustion is one approach to improving ICE thermal efficiency. Biofuels and synthetic fuels can also reduce CO₂ emissions in existing vehicles. Ethanol, a bio-derived fuel, is widely used in varying contents worldwide, and its further utilization is anticipated. This study examines the effects of ethanol blending on emissions, thermal efficiency, knocking, and combustion speed in a super-lean-burn engine. Gasoline surrogates with varying ethanol contents were tested at an excess air ratio (λ) of 2.5. Higher ethanol content reduced nitrogen oxides (NOx) emissions due to lower adiabatic flame temperature. Total hydrocarbon (THC) emissions measured by a Flame Ionization Detector (FID) showed a decreasing trend; however, after correction for low sensitivity to ethanol and aldehydes, no significant differences were observed. Thermal efficiency increased with ethanol content, due to reduced cooling losses. Knocking was mitigated by the higher Research Octane Number (RON) from ethanol blending; however, the extent was smaller than in the production engine operating at λ = 1. This mechanism was examined through ignition delay calculations. At λ = 2.5 and in-cylinder pressures above 9 MPa, the 50–90% combustion duration was prolonged, attributable to suppressed ethyl radical formation under lean conditions and a greater influence of the reaction in which methyl radicals consume hydrogen atoms to produce methane under high-pressure conditions.
Sugata, Kenji, Matsubara, Naoyoshi, Yamada, Ryota, Kitano, Koji
Electrified Propulsion System Balancing for Light Duty Full Size Truck and Sport Utility Vehicles: A 2026 North American Market Perspective2026-01-04124/7/2026
Achieving the stringent EPA CAFE 2032 standards for light-duty full-size trucks and sport-utility vehicles (SUVs) in North American poses significant challenges. While Battery Electric Vehicles (BEVs) offer a clear path to zero tailpipe emissions, their widespread adoption in this segment faces hurdles including range anxiety, payload/towing capabilities, and traditional truck/SUV use cases. This paper investigates a balanced approach, focusing on optimizing propulsion system design with appropriate hardware content, can effectively meet future fuel economy and emissions standards. This investigation examines advanced BEVs and hybrid electric vehicle architectures, including full hybrids (HEVs), and plug-in hybrids (PHEVs) tailored for full-size trucks and SUVs. Considerations include the optimal sizing of internal combustion engines, electric motors, and battery packs to deliver robust performance while maximizing energy efficiency. This paper analyzes the integration of technologies such as electrified transmissions, electric motor configurations, and battery size. Trade-offs between electric motor capabilities, battery pack sizing and emissions reduction across different hybridization levels are investigated. The AMESim Hybrid Optimization Tool (HOT) is used to evaluate multiple propulsion system configurations and drive cycles for energy efficiency. Vehicle selection was performed by evaluating the payload/towing capabilities, propulsion system architecture, and vehicle model year. Drive cycles were selected from truck standards and real-world driving scenarios. The objective is to demonstrate a balanced approach for electrification pathways that satisfy consumer preferences for capability and range, ensuring CAFE 2032 compliance through a diversified powertrain portfolio.
Babcock, Dillon, Robinette, Darrell
A Novel Power-Split Hybrid Electric Architecture for Off-Road Tracked Vehicles: Design and Performance Evaluation2026-01-02584/7/2026
Tracked off-road vehicles operate at low speeds with high tractive effort and frequent skid-steer maneuvers, conditions that push torque and power demand to extremes and exacerbate powertrain efficiency losses. Electrification can improve energy conversion and mobility for such duty cycles. This paper introduces a novel power-split hybrid electric architecture for a tracked vehicle and benchmarks it against three designs: a conventional mechanical driveline, a series hybrid, and a P2 parallel hybrid. To enable fair, architecture-agnostic comparisons, a supervisory controller based on Stochastic Dynamic Programming (SDP) schedules engine operation and power flow across all layouts under representative off-road scenarios, including skid-steer events, with varying terrain and power-demand profiles. Results show higher energy conversion efficiency (lower fuel use) for the proposed power-split architecture, followed by the parallel, then series, and lastly conventional configuration across missions. Beyond efficiency, the proposed architecture offers packaging and robustness advantages: compared with the P2 parallel it eliminates transmission and steering hydraulics, yielding a more compact driveline and compared with the series hybrid it enables smaller traction motors and a smaller battery pack for the same missions. Finally, by allowing the machines to operate below base speed for longer, it extends burst-mode operation without sustained field weakening, thereby reducing demagnetization risk. Study analyzes the reason behind these trends and discusses packaging considerations.
Ghate, Atharva, Sundar, Anirudh, Zhu, Qilun, Prucka, Robert, Figueroa-Santos, Miriam, Barron, Morgan, Castanier, Matthew P.
Methods of Highly Repeatable Lubricant Testing for Electrified Vehicles: Universal Motor Control and Statistical Test-Variation Analysis2026-01-04214/7/2026
This paper describes a systematic approach to evaluate lubricants for hybrid and electric vehicles (xEVs) that can detect impacts on efficiency as low as 0.1 percentage points. Two testing methods were developed to evaluate lubricants’ efficiency effects: (1) on a complete vehicle (using the manufacturer’s hardware and motor control) and (2) on a standalone drive unit (using custom power electronics and control). A Monte Carlo simulation was used to analyze the resulting data to determine the detection limits of the vehicle test method. To evaluate the effectiveness of the test stands and the data-analysis method, a Tesla Model 3 electric drive unit and a Chevrolet Bolt battery electric vehicle (BEV) were characterized for system efficiency. For the Bolt mounted on a hub driven chassis dynamometer, this method is capable of detecting a change in the drive unit’s electromechanical efficiency between baseline and candidate fluids of <0.4 percentage point (pp) with 95% confidence at most of the operating points analyzed. This method can be applied to high-precision testing applications, such as lubricants or additives, cooling systems, gear trains, dynamic seals, bearings, or electric motor designs.
Luo, Yilun, Gross, Michael, Kostan, Travis
Propulsion System Design Considerations for HEV Versus EV Applications2026-01-06414/7/2026
The design and development of EVs and HEVs has become a growing issue recently due to concerns about pollution and dependence on non-renewable fossil fuels. Accordingly, General Motors (GM) has an evolving vehicle electrification plan over the past several decades and into the future to deliver low-cost and efficient EVs and HEVs. Propulsion system requirements for the applications of EV and HEVs are quite different and therefore, the design principles and directions are also distinct between these cases. From micro-hybrid and full plug-in hybrid applications to full EV applications, design requirements, strategies and outcomes can widely vary. Continuous and peak duty are substantially different depending on the application of the vehicle. Motor operational duty is significantly higher for EV compared to the electric motor of a hybrid electric vehicle. Motor torque, power and efficiency requirements are also higher for EV motors, which greatly influences the choice of motor type and its thermal and electromagnetic design. Issues like NVH and thermal can be less significant in designing motors for HEV because of engine masking and lower duty cycle of operation. Motor design requirements, optimization process and results for two different motors intended to be used in EV versus HEV applications are discussed in this paper. Moreover, traction inverter requirements differ significantly across electric vehicles and various hybrid architectures. Each configuration presents distinct challenges—ranging from packaging and thermal management to vibration and electrical constraints. Despite these differences, the design and requirements are harmonized to reduce complexity and ensure seamless performance. This paper outlines the design strategies employed to achieve these objectives.
Momen, Faizul, Jensen, William, Das, Shuvajit, Chowdhury, Mazharul, Alam, Khorshed, Anwar, Mohammad, Reinhart, Timothy
The Impact of Mid-Level Ethanol Blends on Reliability, Performance and Emissions in Gasoline Engine2026-01-03024/7/2026
To reduce CO₂ emissions from automobiles, it is essential to improve system efficiency through the electrification of vehicles with internal combustion engines (ICEs), such as hybrid electric vehicles (HEVs) and plug-in hybrid electric vehicles (PHEVs), as well as through enhancements in ICE thermal efficiency. Additionally, biofuels and synthetic fuels are gaining attention as promising options to reduce CO₂ emissions from existing vehicles. Among these alternative fuels, ethanol, a bio-derived fuel, is already used at varying concentrations in many countries, and its further adoption is expected. Expanding the fleet of flex-fuel vehicles (FFVs) capable of running on high ethanol blends is one approach; however, increasing ethanol content in conventional gasoline, which is more widely used, is considered to have a greater impact on CO₂ reduction. A key issue is how existing vehicles adapt to increased ethanol concentrations such as E20, E30, and E40. This study focuses on turbocharged engines typically found in heavier passenger vehicles, which are less likely to be electrified, to assess the effects of varying ethanol concentrations on performance, efficiency, emissions, and reliability. The evaluation showed that increasing ethanol concentration from E0 to E40 in a fixed Blend stock for Oxygenate Blending (BOB) resulted in comparable or slightly improved torque and thermal efficiency, with emissions remaining similar and abnormal combustion tendencies suppressed. No reliability issues were observed in endurance testing. Furthermore, advancing ignition timing to take advantage of ethanol’s knock resistance within the constraints of mass-produced engines revealed that medium ethanol concentrations are sufficient to realize these benefits. Therefore, to improve output and thermal efficiency across a wider range of vehicles using the same ethanol volume, medium concentrations may be more advantageous than higher concentrations.
Matsubara, Naoyoshi, Sugata, Kenji, Koyama, Takashi, Ochi, Yuta, Aoki, Mizuki, Hashima, Takashi, Kodama, Kohei, Tomoda, Keiju, Kojima, Masakiyo
Development of a Zeolite-Based (HC/NOx Trap Type) Cold-Start Catalyst (CSC) for Meeting Tier4/LEV IV Tailpipe Emission Standards, Part IV2026-01-03644/7/2026
This paper is a follow-up study to three preceding reports [1,2,3] that focus on the development of a β-zeolite-based hydrocarbon/nitrogen oxide (HC/NOₓ) trap-type cold-start catalyst (CSC) — a cost-efficient technical strategy for meeting the increasingly stringent vehicle tailpipe emission standards for automotive exhaust systems, including Tier 4 and LEV IV, which are to be enforced in the near future. A core challenge in meeting Tier 4 and LEV IV exhaust emission standards lies in the fact that both the SC03 and US06 test cycles commence from ambient (cold) temperatures, as opposed to the elevated (hot) starting temperatures mandated for the preceding Tier 3 and LEV III standards. In the present study, a hybrid electric vehicle (HEV) fitted with two distinct Tier 3-certified exhaust aftertreatment systems—one officially certified to Bin 30 standards and the other a Bin 20-equivalent system (non-officially certified)—was subjected to testing under the cold SC03, cold US06, hot SC03, and hot US06 test cycles for the purpose of comparative analysis. To meet the Tier 4/LEV IV Bin 30 engineering target of 13.13 mg/mile for combined NOₓ+NMHC tailpipe emissions, the HEV with the Tier 3 Bin 30 system required an approximate 64% reduction in tailpipe emissions during cold SC03 tests, while the HEV with the Tier 3 Bin 20 system needed a 52% reduction. For cold US06 tests, these two HEVs required emission reductions of 50% and 38%, respectively, to achieve the same target. The higher tailpipe emissions observed in cold tests (relative to hot tests of the same cycles) are attributed to elevated cold-start emissions. The CSCs developed in this work were applied to modify the Tier 3 Bin 20 aftertreatment system, and vehicle tests were conducted with the CSC-modified systems under both cold SC03 and cold US06 cycles. Notably, the CSCs effectively reduced cold-start tailpipe emissions (NOₓ+NMHC) in both test cycles, enabling the HEV to meet the Tier 4/LEV IV Bin 30 engineering target of 13.13 mg/mile for NOₓ+NMHC tailpipe emissions. Detailed emission results, along with the effects of zeolite loading and Pd loading on CSC performance, were also investigated and are discussed in this manuscript.
Xu, Lifeng, Wei, Hong, Zhao, Pengfei, Ma, Ruibo, Wang, Lin, Qian, Wangmu, Qian, Menghan
Development of a Model-Aware Data-Driven Control Algorithm for a Drive-by-Wire System for a Level 4 Automated Vehicle2026-01-00434/7/2026
Precision control in Level 4 Automated Vehicles is essential for enhancing operational efficiency, accuracy, and safety. This work, conducted as part of ARPA-E’s NEXTCAR program, focuses on developing a robust hardware and software control solution to enable drive-by-wire functionality. A previous publication by the authors presented the hardware solutions for overtaking stock vehicle controls. This paper focuses on a model-based and data-driven control algorithm to enable drive-by-wire functionality for longitudinal and lateral motion control for a 2021 Honda Clarity Plug-In Hybrid Electric Vehicle. This vehicle was equipped with a set of sensors and an onboard processing unit to enable Level 4 automation. For lateral controls, an algorithm was developed to command steering torque to the electronic power steering module, ensuring the vehicle could attain the desired steering angle position at varying speeds. The system leveraged feedforward and feedback mechanisms. Feedback controller gains were identified through frequency response analysis of the steering torque assist electric motor and were further refined during track testing. To optimize the controller’s response time, a feedforward function was developed using a physics-aware model of the vehicle's steering system. The independent feature selection for the model was guided by using the physics of the system. For longitudinal control, the control inputs included the positions of the brake and accelerator pedals sent to the stock ECU, with the desired speed as the setpoint. The setup used a combination of feedforward and feedback control to achieve the target acceleration or deceleration. These algorithms underwent extensive dynamometer and track testing to perform various maneuvers in conjunction with the automated driving system.
Adsule, Kartik, Bhagdikar, Piyush, Drallmeier, Joseph, Alden, Joshua, Gankov, Stanislav
Engine Park Angle Control via Electric Machine under Varying Deceleration Limits2026-01-04454/7/2026
Accurate control of the engine park angle during Autostop in hybrid vehicles is critical for enabling rapid and smooth Autostarts, reducing start-up vibrations, and enhancing overall driving comfort. However, in real-world scenarios, the available torque for engine positioning is often limited by competing driver torque demands, battery discharge constraints, and the state of charge (SoC). Under these conditions, conventional position-speed control strategies frequently fail to achieve the desired precision. This paper introduces an adaptive control strategy for the electric machine (EM) that drives the internal combustion engine, ensuring precise alignment of the crankshaft at a predefined angle to optimize restart conditions. Upon receiving an engine shutdown request, the proposed controller computes an adaptive deceleration profile that respects the EM’s torque and deceleration limits while guiding the crankshaft toward the target park position. The core of the approach lies in generating a theoretical speed trajectory and tracking it through an adaptive nonlinear control law that dynamically adjusts in real time to compensate for disturbances and eliminate residual angular error at the end of the maneuver. Unlike conventional methods, the proposed solution maintains robustness under stringent deceleration constraints and varying operating conditions. Simulation and experimental results on a hybrid powertrain test bench demonstrate that the proposed method significantly improves park angle accuracy and consistency even under limited deceleration scenarios.
Purohit, Punit, Achir, Ali, Bhakare, Allwyn
Comparison of Ammonia Emission Characteristics Between Different Gasoline Vehicles Equipped with Three-Way Catalysts2026-01-03744/7/2026
In recent years, the tightening of vehicle emission regulations has led to a decreasing trend in regulated pollutants such as NOₓ and CO. However, the emission of ammonia (NH₃), which is unintentionally generated during the purification process in three-way catalyst of gasoline vehicles, has become a growing concern. NH₃ emissions from vehicles can serve as a precursor to PM2.5 and have been reported to cause local roadside pollution. Therefore, there is a growing need for on-road testing to identify conditions under which NH₃ is likely to be emitted. Furthermore, since engine control strategies vary among vehicle types, it is desirable to consider differences in emission behavior across different models. In this study, on-road NH₃ emissions were measured for multiple vehicle models with different powertrains, and the effects of engine behaviors and engine operating duration across vehicles on NH₃ emissions were investigated. To analyze differences in NH₃ emission behavior among vehicle types, conventional gasoline vehicles and series-type hybrid vehicles were employed. Additionally, vehicle control parameters were obtained via an OBD (On-Board Diagnostics) interface unit and utilized for analysis. The analysis revealed that, for the conventional gasoline vehicles, aggressive accelerator pedal control induced rapid fluctuations in engine speed, which in turn led to NH₃ emissions. In contrast, for the series-type hybrid vehicles, NH₃ emissions were primarily observed when the engine started under specific conditions, whereas differences in driver behavior had only a minor direct impact on NH₃ emissions. In addition, longer engine operating durations resulted in higher emission levels. A common characteristic observed across both vehicle types was that NH₃ emissions were elevated during periods corresponding to CO emissions, which serve as precursors to NH₃ formation.
Ashizawa, Keigo, Fukunaga, Chisato, Gao, Tianyi, Sato, Susumu
Multi-Body Dynamics Control Integration Tool Application in Hybrid Vehicle System Identification2026-01-04174/7/2026
The multi-body dynamics (MBD) model and the MATLAB Simulink model can be integrated to create a control-integration model. Using a high-fidelity MBD model to represent the vehicle as the plant, this integrated model can be used to analyze vehicle system physics and develop control strategies. For hybrid vehicles, this process is more complex because the powertrain and other vehicle systems are often built as separate MBD models. This paper describes a method for integrating a powertrain model developed in AMESIM, a vehicle model developed in SIMPACK, and a control model developed in MATLAB Simulink. The resulting integrated model was then used to perform frequency sweep analysis to identify driveline system properties. In particular, the driveline frequency and the amplitude of the transfer function between motor speed and motor torque are critical parameters. By applying active damping control to the driveline system, the peak amplitude and driveline vibrations can be reduced. The hybrid vehicle studied includes a transmission system with ten different gears. When the vehicle operates at different gear level, the system behaves differently. The analysis results can assist the driveline control team in developing appropriate strategies to improve overall vehicle performance.
Xing, Xing, Mathew, Vino
Meeting the Challenges of PHEVs/REEVs Lubrication: Insights from Comprehensive On-Road Fleet Tests2026-01-03544/7/2026
Driven by increasingly stringent emissions regulations, rapid advancements in electrification technologies, and rising consumer demand for fuel-efficient and environmentally sustainable mobility, Plug-in Hybrid Electric Vehicles (PHEVs) and Range-Extended Electric Vehicles (REEVs) have seen substantial growth in the global automotive market. These hybrid architectures integrate electric propulsion with Internal Combustion Engines (ICEs), offering extended driving range and operational flexibility. However, the evolution of hybrid powertrain systems introduces distinct operating characteristics—such as frequent engine start-stop events, reduced average engine loads, and extended oil drain intervals—that diverge significantly from conventional ICE vehicle usage profiles. These changes present new challenges for engine lubricants, which must maintain performance under intermittent engine operation, increased exposure to water and fuel, and fluctuating thermal and environmental conditions. Conventional lubricant formulations, designed for continuous ICE operation, may not sufficiently address the demands of hybrid applications, where concerns such as oil degradation, wear protection, deposit control, and compatibility with aftertreatment systems are increasingly critical. Consequently, there is a growing need to redefine lubricant performance criteria to ensure oils are qualified to meet the specific demands of hybrid powertrains. This study presents a comprehensive evaluation of engine lubricant performance in PHEVs and REEVs, based on extensive field testing under diverse real-world operating conditions. Unlike prior research which focused on oil emulsification and water entrainment, this work focuses on four underexplored yet industry-relevant aspects: 1 Piston cleanliness: Under typical PHEV operating conditions, and after accounting for variations in driving-cycle characteristics, additive technologies incorporating salicylate detergents and elevated treat rates demonstrate substantial effectiveness in reducing piston deposit formation. 2 Long-term aging in simulated parked condition: Simulated aging tests with used oils (15,000 km and 30,000 km) over a two-year period showed stable values in key lubricant parameters including Kinematic Viscosity (KV), Total Base Number (TBN), Total Acid Number (TAN), and oxidation. 3 Oil Degradation: For REEVs equipped with ICE featuring exhaust gas recirculation (EGR) system, particularly those of the non-plug-in type, high-performance engine oils with enhanced resistance to nitration can help to ensure adequate protection and long-term durability. 4 Lubricant compatibility with Gasoline Particulate Filter (GPF): The reduced ICE engagement in modern PHEVs and REEVs leads to lower ash accumulation, thereby enabling the potential use of higher-ash engine oils in GPF-equipped hybrid vehicles without compromising filter durability performance.
Zhang, Ruifeng, Andrew, Rhiann, Hu, Gang, Lim, Pei Yi, Lu, Hongjie, Moizan, Simon
In-Use Life Digital Twin (Redundant Storage) and Swappable Use Case for Battery Durability2026-01-03974/7/2026
As regulatory frameworks for zero-emission vehicles (ZEVs) and battery electric vehicles (BEVs) continue to evolve, there is growing emphasis on monitoring battery durability and usage throughout the vehicle lifecycle. These regulations increasingly specify the use of data monitors and tracking mechanisms to assess battery health and performance. In addition, regulations require anti tampering mechanisms especially for monitors that have external write access. Historically, regulations focused primarily on vehicle warranty; however, with the introduction of battery durability monitors, clarity is needed for the new battery durability monitors. More specifically if the battery durability monitors track with the lifetime of the vehicle or if they follow the lifetime of the battery. Furthermore, current regulations provide no guidance on high-voltage (HV) traction battery service strategies or methods to protect monitors from tampering by external customers. This paper will classify battery durability tracking parameters (DIDs) according to whether they align to the lifetime of the vehicle or the battery itself. Building on this classification, a service strategy is proposed that considers typical vehicle architectures: when the battery management Electrical Computer Unit (ECU) is fully integrated with or separated from the high voltage traction (HV) battery. The outlined service strategy not only supports regulatory compliance, but also enhances data integrity by mitigating the risk of tampering with monitored parameters through a Digital Twin framework. More specifically, the Digital Twin framework introduces redundant storage of critical information in multiple storage locations such as ECUs and then a mechanism for correlating that critical information to determine a mismatch. This approach anticipates future requirements for tamper-proofing and ensures secure, reliable tracking of battery durability metrics through redundant ECU storage.
Laskowsky, Patricia, Bunnell, Justin, Zettel, Andrew, Albarran, Josue
Identifying Patterns of Real-World Charging Frequency for a Sample of Plug-In Hybrid Electric Vehicles in North America2026-01-04294/7/2026
Plug-in Hybrid Electric vehicles (PHEVs) have the capability to effectively utilize electricity from the grid as an energy source for powering an appreciable portion of the total vehicle miles travelled (VMT), thereby reducing greenhouse gas (GHG) emissions, since the Carbon Intensity (CI) of electricity is often less than that of liquid fuels in many parts of the world. Several real-world usage factors can affect the fraction of VMT electrified, with the frequency of charging being one of the most influential factors. Studies in recent years have attempted to characterize the real-world performance of PHEVs based on long-term average fuel consumption and/or other data flags in the readout from vehicle On-Board Diagnostics (OBD), but such approaches are unable to infer accurate estimates for the occurrence of charging events. This paper adopts an approach that relies on analysis of highly granular (trip by trip) information obtained from vehicles equipped with a data communication module (DCM) to infer the occurrence of charging events from change in the battery state of charge (SoC) between trips. Analysis of data obtained from a large sample of PHEVs (one full calendar year for hundreds of vehicles) in the US and Canada reveals three distinct patterns: i) vehicles that are consistently charged, ii) vehicles that are consistently not charged, and iii) vehicles with temporally varying frequency of charging. Unlike some other studies about PHEVs in other parts of the world, results of our sample for PHEVs in North America show that the majority are consistently charged, but with various frequency levels that are regionally dependent.
Hamza, Karim, Laberteaux, Kenneth
Real-Time Observations of the Effect of Fuel Dilution in an Engine Transient Friction Rig. Along with Real-Time Observations of Fuel Entering and Leaving Internal Combustion Engine Oil, over Both Standard Engine, ICE and Plug-In Hybrid, PHEV Dynamic Drive Cycles2026-01-03514/7/2026
Hybrid electric vehicles (HEVs) with an increasing level of electrification, are becoming a major part of the global energy transition. To achieve lower engine tailpipe exhaust emissions and improve total fuel consumption, typically the HEV control system expertly and frequently switches between the internal combustion engine and electric motor drive, with multiple stops and restarts of the internal combustion engine (ICE). As a consequential result of this switching, are typically slower or even incomplete engine warm-up times, depending on the engine speed, load pattern and run time of the vehicle drive cycle. Along with the speed and load transient control, the engine stop and start processes are also challenging to control, with respect to cold start fuel and combustion by-products entering the oil. Consequently, contamination enters the engine oil but may not completely leave. These effects are highly transient over the drive cycle. Contaminants and in particular, fuel dilution, will affect the engine oil viscosity. To demonstrate this whilst yielding insights, a precisely controlled engine test cell, running the cold start Worldwide Harmonized Light Duty Transient Cycle (WLTC) for both, a non-hybridized ICE only vehicle and a HEV in charge sustaining mode operation is described. This also has on-line viscosity sensing and oil sampling. Typical data is shared along with engine oil comparisons. For complimentary insights, the impact of the fuel dilution on engine friction was investigated using a novel, precise, fully transient engine friction test rig, which measures gasoline direct injection high pressure fuel-pump friction and engine oil viscosity accurately. The cycle is based on measured data from vehicles tested on a chassis dynamometer. On-line friction data, with oil comparisons is used to show real-time data of the effect of fuel dilution on the frictional energy required, thus CO2 over the full WLTC.
Butcher, Richard, Bradley, Nathan, Thedering, Dennis
Development of Honda S+ Shift Utilizing e:HEV System2026-01-04184/7/2026
Honda is promoting mobility electrification to realize a carbon-neutral society by 2050. Hybrid vehicles will remain advantageous over electric vehicles in terms of manufacturing cost and driving range until renewable energy usage increases, charging infrastructure is sufficiently developed, and battery costs are reduced. In response to this situation, Honda has developed a new control system, “Honda S+ Shift”, which further enhances the “emotional value of driving pleasure” inherent to the e:HEV system and creates new value for hybrid vehicles. Honda S+ Shift synchronizes the engine and vehicle speed and selects a virtual gear position according to the driver's operation such as acceleration, cornering, and deceleration. Subsequently, the system achieves the required system output in cooperation with a dedicated energy management system. It also works with each vehicle system, such as drive force control, sound control, and meter cluster, to stimulate all five senses of the driver, greatly enhancing synchronization between the driver's senses and vehicle behavior. This paper explains how the concept of Honda S+ Shift is realized with the e:HEV system. Since there are no mechanical gear restrictions, Honda S+ Shift can select each gear ratio freely and enables fast shifting. On the other hand, there are difficulties in realizing realistic shifting behavior without direct connection between an engine and tires. Furthermore, e:HEV has three specific operation modes: EV, Hybrid and Engine, and Honda S+ Shift has to utilize them to keep its high efficiency. The first part of this paper describes the setting of the gear ratios, drive force and deceleration. Next, it explains engine speed control to realize sharp shifting and traction motor control to produce a realistic shift feel. Then, it describes how Honda S+ Shift utilizes three modes of e:HEV. It also refers to cooperation with sound and meter cluster control to maximize its effects.
Murata, Naoya, Narimoto, Ryosuke, Saito, Masatoshi, Ishida, Daichi, Gunji, Hiroki, Mitogawa, Terumasa, Ukai, Yohei, Kurachi, Shinobu, Nagakura, Akari, Shiki, Kazuki, Maeda, Sadaharu
First Drive: 2027 Mercedes-Benz CLA Hybrid26AUTP03_133/1/2026
It's a crisp day in the Austrian Alps. A closed road has been plowed just for us. Well, piles of snow have been pushed aside, but the road remains covered in white. This is the type of drive usually reserved for an SUV or all-wheel-drive outfitted vehicle sporting cladding and a robust following amongst dog owners. Instead, I'm behind the wheel of the 2027 Mercedes-Benz CLA hybrid, and everything is going great. Well, mostly everything. The 2027 CLA hybrid uses one of two powertrains coming to the German sedan, alongside an electric version. Both will be available in the second half of 2026, according to Mercedes, and both are built on the new MMA (Mercedes Modular Architecture) platform. A platform that supports both EV and ICE powertrains, Mercedes says, allows the company to meet customer demand.
Baldwin, Roberto
Development of BYD Flat Engine for Luxury Hybrid Vehicles03-19-02-00072/24/2026
To meet the requirements of luxury hybrid vehicles regarding engine power, torque, size, and NVH performance, BYD independently developed a 2.0 T flat engine. Designs such as increased intake valve lift, widened intake valve profile, swept piston bowl, and extended exhaust backflow region optimized in-cylinder airflow, enabling the BYD flat engine to achieve a maximum power of 180 kW and a peak torque of 380 N·m. This engine is 820 mm in length, 430 mm in width, and 420 mm in height, saving approximately 45% in volume compared to a competitor engine. The lubrication challenges of the flat engine were addressed through the coordinated implementation of a dry sump system, a multifunctional oil pump, and piston ring orientation design. A novel parameterized modal analysis methodology (considering phase and amplitude) was used for optimizing NVH performance. In synergy with the sandwich-type soundproof plates and four-sided acoustic encapsulation, the noise level (1-m sound pressure level, four-point averaged) of the BYD flat engine is 2.2~2.9 dB(A) lower than the lower limit of AVL’s scattering band. Owing to its desirable performance in power output, packaging compactness, and NVH characteristics, the BYD flat engine has been integrated into the powertrain of the Yangwang U7 model.
Pan, Shiyi, Zhang, Nan, Wang, Qiang, Liu, Jun, Liu, Jing, Xu, Zhiqin, Zheng, Junli, Li , Cunshuo
Development of Plug-In Hybrid Motorbike and Analysis towards Sustainable Urban Mobility2026-28-01112/12/2026
The transportation system is one major catalyst to urban ecological imbalance. In developing countries, two-wheelers are considered a major mode of urban personal transportation because of their compactness, easy maneuver in heavy traffic and good fuel efficiency. In India, middle and lower middle-class people prefer to choose two wheelers, and these vehicles are dominantly fuelled by gasoline. Although, the energy consumption by a two-wheeler is comparatively less than that of a four-wheeler, they use about 60% of the nation’s petroleum for on-road vehicles and the impact on urban air quality and climatic change is significantly high. This high proportion of gasoline utilization and emission contribution by two wheelers in cities demand greater attention to improve urban air quality and near-term energy sustainability. Electrification of two-wheelers through the application of a plug-in hybrid idea is a promising solution. A plug-in hybrid motorbike was developed by putting forth a novel drive technique, which demonstrated the advantages of reducing greenhouse gas emissions and using less fuel. The experimental investigation reveals noticeable petroleum fuel savings and greenhouse emission reduction. Through the installation of a hub motor in the rear wheel, the dynamic behaviour of the prototype was examined and observed marginal changes in ride parameters. A cost-benefit analysis was also performed to estimate the payback period for the additional cost incurred.
Kannan, Prashanth, Shaik, Amjad, Talluri, Srinivasa Rao
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