Browse Topic: Electric vehicles

Items (5,026)

Cradle-to-grave assessment of Austrian passenger car traffic based on actual vehicle movements and derivation of future forecasts for minimising greenhouse gas emissions

2026-01-0457To be published on 04/07/2026

As part of the decarbonisation process for passenger car fleet in Austria, battery electric cars in particular have been subsidised in recent years, as these vehicles are considered to be largely emission-free during use and are expected to reduce emissions in future. However, in order to sustainably reduce the global greenhouse gas emissions of Austrian passenger car traffic, taking into account all types of propulsion systems, it is necessary to apply a cradle-to-gate approach, as is commonly done in comparable analyses in the literature, which evaluates the emissions of the entire vehicle life cycle. The most important phase in the life cycle assessment remains the well-to-wheel phase, which includes emissions from energy supply and vehicle use. Due to the large number of influencing factors, highly simplified models are usually used for this phase in the literature. As part of this work, a methodology was developed that, allows an in-depth analysis of entire vehicle fleets by

Lischka, Gregor, Tober, Werner

New Inverter Switching Control Method to Enhance Sound Quality for Electric Vehicles

2026-01-0437To be published on 04/07/2026

Conventional inverter control uses a fixed switching frequency, which leads to a high-pitched switching noise in electric vehicles (EVs) that does not vary with vehicle speed. Although EVs are generally much quieter than traditional internal combustion engine (ICE) vehicles, some EV owners complain about the lack of dynamic driving sound feedback. A new patented technology has been developed to enhance EV sound quality by dynamically controlling the inverter switching frequencies. This technology generates dynamic propulsion sound with new "switching order" features at multiple harmonics, with the pitch proportional to vehicle speed. A fixed pulse ratio between the switching frequency and the electric motor RPM is implemented to control the switching order. This reduces switching losses during low-speed operation and provides boosted acoustic feedback to the driver during acceleration, which enhances driving experience during sports driving. Furthermore, a special "EV shifting" sound

He, Song, Gagas, Brent, Welchko, Brian, Ball, Kerrie, Gong, Cheng

In-Use Life Digital Twin and Swappable Use Case for Battery Durability

2026-01-0397To be published on 04/07/2026

In-Use Life Digital Twin and Swappable Use Case for Battery Durability By: Patricia Laskowsky, Josue Albarran, Justin Bunnell, and Andrew Zettel Abstract The UN GTR 22 is required as part of the Environmental Protection Agency’s legislative rulemaking for multi-pollutants emission standards for model years 2027 and later light-duty and medium duty vehicles. The EPA claims it has the right to govern requirements on ZEVs and BEVs. ZEVs, in their viewpoint, are “emission related” because it enables the vehicle to produce zero emissions. With the adoption by the EPA under its Tier 4 regulations of the UN GTR 22, comes several new tracking DIDs, Data Identifiers. These DIDs are tied battery durability and energy tracking They track conditions and usages of electric vehicles that may accelerate the loss of electric range and/or loss of efficiency of the propulsion energy storage and delivery. More specifically, tying these trackers to EPA emission related discussion, the loss of electric

Laskowsky, Patricia, Bunnell, Justin, Zettel, Andrew, Albarran, Josue

Behavioral Determinants of Electric Vehicle Battery Degradation: Evidence from Large-Scale Real-world Operations

2026-01-0458To be published on 04/07/2026

Electric vehicles (EVs) are central to sustainable transport, yet battery service life remains a limiting factor for cost and adoption. Distinct from traditional laboratory-based simulations that often fail to capture the complexity of field conditions, this study investigates how EV user behavior—including driving style and charging demands—influences capacity using large-scale, real-world operational data from daily EV usage. A data-driven framework is developed to quantify driving and charging behaviors through multidimensional feature extraction at the vehicle level and estimate battery State-of-Health (SOH) trajectories, enabling direct linkage between individual behavior patterns and degradation outcomes. Results reveal substantial heterogeneity in aging rates explicitly driven by diverse user behaviors: under identical urban conditions, vehicles with a radical driving style exhibit approximately 81% faster SOH decline per 20,000 km than those with a moderate style ; regarding

Liu, Tianyi, Jing, Hao, Zhu, Jiankuan, Chen, Yongjian, Ou, Shiqi(Shawn), Qian, Xiaodong

Data-driven feedforward compensation-based trajectory tracking control

2026-01-0028To be published on 04/07/2026

Advanced autonomous driving is a critical component in the intelligent development of new-generation electric vehicles. Research on reliable chassis control algorithms ensures the safety and stability of autonomous vehicles during operation. To enhance the control performance of autonomous vehicles and improve the accuracy of trajectory tracking, this paper proposes a data-driven feedforward compensation trajectory tracking control approach. By optimizing the design of the feedforward compensation loop, systematic errors and latency in the vehicle’s steering system are mitigated, thereby enhancing the precision and robustness of the control algorithm. Initially, the paper analyzes the control errors present when the vehicle responds to controller commands. Subsequently, the paper focuses on the steering angle errors in trajectory tracking, identifying and analyzing the most relevant factors. A time-delay neural network (TDNN) based on data-driven principles is designed to model and

Yang, Yijin, Yuan, Yin, Wang, Zhenfeng, Su, Ailin, Zhang, Zhijie, Lu, Yukun

Climate Heat Recovery Energy Study in Electric Vehicles

2026-01-0129To be published on 04/07/2026

Climate control systems in Battery Electric Vehicles (BEVs), Plug-in Hybrid Electric Vehicles (PHEVs), and Extended Range Electric Vehicles (EREVs) rely on electrical energy to provide cabin heating. In winter conditions, the absence of waste heat from internal combustion engines necessitates increased energy consumption for thermal comfort, which directly impacts vehicle range. Conventional HVAC systems typically operate with a mixture of cold ambient air and recirculated cabin air. However, the proportion of recirculated air is limited due to windshield fogging risks, constraining energy-saving potential. To address this, MAHLE has developed modular heat recovery technologies that utilize the thermal energy of exhaust cabin air, that would normally leave the passenger compartment through vehicle body vents, to precondition incoming fresh air, thereby reducing the heating load. These solutions are engineered for scalable integration into existing HVAC architectures, allowing

Wolfe, Edward, Wochele, Kerstin, Reid, Bailey

Research on Reliability Test Methods for Electric Drive Axle Differentials

2026-01-0007To be published on 04/07/2026

With the rapid socio-economic development, global issues such as the energy crisis and environmental pollution have become increasingly severe. Electric vehicles have garnered growing attention due to their environmental friendliness, simple structure, and high energy efficiency. Electric drive technology is regarded as the most ideal universal driving solution for pure electric vehicles, hybrid electric vehicles, and fuel cell vehicles. The electric drive axle, as a new type of integrated mechatronic transmission system, is being increasingly adopted owing to its advantages such as high drive efficiency, flexible spatial arrangement, and facilitation of digital and automated chassis control. This study focuses on reliability testing methods for the differential in electric drive axles, mainly including the extraction of reliability test conditions and feasibility analysis of the test scheme. The main research contents are as follows: First, based on specific parameters of an electric

Zheng, Hongyu, Li, Ziyu, Wang, Dajiang, tian, kai

Signal Integrity in Distributed BMS: Reliable SPI and Ethernet Communication for Next-Gen EVs

2026-01-0171To be published on 04/07/2026

Distributed battery management systems (BMS) are critical for scaling electric vehicle packs to hundreds of cells, but reliable high-speed communication between modules remains a challenge. Daisy-chained SPI and CAN FD are widely deployed today, while Ethernet is being evaluated for next-generation systems that require higher bandwidth, synchronization, and diagnostics. This paper examines the signal integrity (SI) challenges facing distributed BMS communication, including skew, jitter, crosstalk, and electromagnetic interference (EMI) across PCB traces and wiring harnesses. HyperLynx and SPICE-based simulations are combined with experimental results on a 192-cell test platform to quantify the impact of layout constraints, impedance mismatches, and harness parasitics. Results show that poor SI design can reduce signal margins by more than 18 dB, leading to data corruption and diagnostic failures. Co-design strategies for PCB routing, termination, and shielding are proposed, achieving

Abdul Karim, Abdul Salam

Effect of housing design on oil splash lubrication in an E-drive Unit through Computational Fluid Dynamics Simulation

2026-01-0116To be published on 04/07/2026

Proper lubrication of gears and supporting bearings is crucial for the optimal functioning of an e-drive unit, particularly under high-speed and high-load conditions. Understanding the causes of bearing failure requires an analysis of the oil splash pattern in a testbed with a transparent casing. Additionally, modifying the gearbox and housing designs can be both time-consuming and costly to achieve performance goals. As an alternative, Computational Fluid Dynamics (CFD) modeling provides a virtual testing environment that allows for quicker design evaluations and reduces product development time. This study focuses on using CFD to assess a housing design aimed at enhancing lubrication for the rear and front drive units (RDU/FDU) in electric vehicles. Multiphase flow simulations were conducted using the volume of fluid (VOF) method in the commercial CFD software Simerics-MP+. This software generates an unstructured Cartesian mesh and manages complex mesh movements through a volume

Kumar, P. Madhan, Motin, Abdul, Pasunurthi, Shyam Sundar, Ganamet, Alain, Maiti, Dipak, Taghizadeh, Salar, Mohapatra, Chinmoy K.

Navigation Integrated End-to-end Path Planning Development and Vehicle Testing

2026-01-0032To be published on 04/07/2026

In order to achieve fully autonomous driving, point to point autonomous navigation is the most important task. Most existing end-to-end models output a short-horizon path which makes the decision process hard to interpret and unreliable at intersections and complex driving scenarios. In this research, we build a navigation-integrated end-to-end path planner on top of an openpilot open source model. We created a navigation branch that encodes route polyline geometry, distance-to-next-maneuver, and high-level instructions and combines with path plan branch using residual blocks and feed-forward layers. By adding minimal parameters, new model keeps the original openpilot tasks unchanged and have the path output based on the navigation information. The model is trained on diverse urban scenes and lighting conditions, and it shows improved route adherence in vehicle testing. The proposed model is validated in a comma 3x device installed on a 2025 Nissan Leaf test vehicle. The road test

Wang, Hanchen, Li, Taozhe, Hajnorouzali, Yasaman, Burch, Collin, li, Victoria, Tan, Lin, Arjmanzdadeh, Ziba, Xu, Bin

Method of Estimating Electric Vehicle Charge Time Based on Neural Networks

2026-01-0382To be published on 04/07/2026

Accurate prediction of electric vehicle charging time is critically hindered by dynamic, non-linear factors including battery aging which is indicated by the State of Health (SOH), substantial power diversion to thermal management systems in extreme temperatures, fluctuating user-defined accessory loads, and hardware limitations of the charging infrastructure. Traditional estimation methods, reliant on static models or predefined calibrations, fail to adapt to these real-world variables, leading to inaccurate predictions and user dissatisfaction. This paper presents a novel data-driven estimation framework utilizing a tailored feedforward neural network architecture specifically designed for this complex task. The model processes a sensitive set of inputs—including initial State of Charge (SOC), SOH, battery temperature, charging station power level and user-selected target SOC—to effectively capture the intricate, non-linear interdependencies governing the charging process. The

Xie, Zhentao, shojaei, Sina, Weslati, Feisel

Electrified Propulsion System Balancing for Light Duty Full Size Truck and Sport Utility Vehicles: A 2026 North American Market Perspective

2026-01-0412To be published on 04/07/2026

Achieving the stringent EPA CAFE 2032 standards for light-duty full-size trucks and 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

Babcock, Dillon, Robinette, Darrell

Effects of Obstacle Height and Vehicle Roll Behavior on Electric Vehicle Side Impact Safety

2026-01-0405To be published on 04/07/2026

Electric vehicles (EVs) face unique safety challenges under pole side impact conditions, largely due to the presence of floor-mounted battery packs. Existing regulatory test procedures, such as Federal Motor Vehicle Safety Standards (FMVSS) 201, primarily address occupant injury using full-height cylindrical obstacles. These procedures were originally developed for internal combustion vehicles (ICVs). However, real-world roadside crashes frequently involve obstacles of varying heights, such as guardrails, curbs, and median bases. While these obstacles pose limited risk to the passenger compartment, they can intrude into the battery pack and trigger thermal runaway. This study investigates the influence of obstacle height on EV pole side impacts. Finite element simulations of a commercially available sedan were conducted against rigid obstacles of different heights. Results reveal a non-monotonic trend of battery intrusion governed by the interplay between rollover dynamics and

Ma, Chenghao, Xing, Bobin, Zhou, Qing, Xia, Yong

Architecture-Driven Fixed-Point Scaling for AUTOSAR-based ECUs: A Production-Feasible Architecture for Centralizing Scaling Semantics

2026-01-0069To be published on 04/07/2026

Floating-point arithmetic is widely used in automotive embedded software to scale Controller Area Network signals and calibration parameters with fractional factors such as 0.1. However, floating-point operations, even on microcontrollers equipped with floating-point units, can increase execution time and CPU load. In AUTOSAR architectures, converting floating-point scaling to fixed-point is not trivial because scaling semantics must be integrated consistently across components, yet AUTOSAR platform toolchains offer only limited automation at the Application Data Type level. Although CompuMethod definitions can express scaling, integration typically remains manual and distributed across application software components, reducing consistency and reusability. This study presents an architecture-driven methodology that formalizes fixed-point scaling as a centralized architectural service, realized through a parser-driven fixed-point macro generation pipeline. Standardized CAN DBC and

Lee, Hoseok, Ko, Donggun

Techno-Economic Evaluation of Electified Vehicle Options in Drayage Fleets

2026-01-0454To be published on 04/07/2026

The transition of drayage fleets from diesel to battery electric vehicles (BEVs) poses both opportunities and uncertainties, especially regarding long-term economic viability. While total cost of ownership (TCO) is a useful benchmark, fleet operators and investors are equally concerned with investment performance metrics such as payback period and Internal Rate of Return (IRR), which better reflect financial risks and investment return timelines. This study proposes a comprehensive framework to evaluate the economic feasibility of transitioning from diesel to BEVs, jointly analyzing TCO parity conditions, payback periods, and IRRs under different technology, cost, and operational scenarios. Building on a previously developed cost modeling tool, the analysis incorporates evolving battery prices, energy costs, vehicle performance characteristics and other assumptions from 2025 to 2050. Real-world duty cycle data from a Class 8 drayage fleet at the Port of Savannah is used to capture

Sun, Ruixiao, Sujan, Vivek, Goulet, Nathan, Wang, Qixing

Understanding the Effects of Process Parameters on the Dispense Uniformity of Elastomeric Silicone Coating Material for Automotive Manufacturing.

2026-01-0239To be published on 04/07/2026

As electric vehicle (EV) manufacturing scales, innovative approaches have been evolving for battery fire protection materials to mitigate thermal runaway hazards, including fire and blast protective coatings. These materials often exhibit high-viscosity and must be deposited with uniform thickness and stable geometry to ensure reliable thermal barriers and battery pack integration. In practice, coating uniformity (uniform thickness, edge fidelity, and minimal sag/run prior to cure) is highly sensitive to dispense conditions, including nozzle slot width, nozzle length, effective dispense height (stand‑off), nozzle sweep speed, and volumetric dispense rate. Establishing robust process understanding early is therefore essential to avoid start‑up scrap, rework, and variability downstream. This paper presents a combined computational and experimental methodology to optimize and de‑risk dispensing of elastomeric battery fire protection (BFP) coatings. We develop a physics‑informed modeling

Hossain, Arif, Repollet Pedrosa, Milton H., Norquest, Kade, Mcmichael, Jonathan, Ng, Sze-Sze, Aradhyula, Pranavi, Thomas, Ryan, Gorin, Craig, Dietsche, Laura, Kenney, James A.

Plug-in Electric Vehicles Adoption: A Review of Forecasting Methodologies, Policy Impacts, and Future Trajectories in Major Global Markets

2026-01-0455To be published on 04/07/2026

Accurate forecasting of Plug-in Electric Vehicle (PEV) market sales share is vital for evidence-based policymaking, yet existing studies employ diverse and often fragmented methodologies, creating a need for systematic review to clarify their analytical foundations and comparative strengths. This study classifies mainstream forecasting methodologies into theory-driven and data-driven approaches, providing a review of five representative models' merits, limitations, and potential directions. Analysis reveals that leading approaches increasingly employ cross-scale model coupling, theory-data fusion, and modular design to harness complementary strengths, improving model robustness and predictive accuracy. Furthermore, the study compares PEV policies and market forecasts in China, the United States, and Europe—the world's three largest automotive markets. The findings indicate a strong linkage between forecast convergence and policy stability. China demonstrates the highest policy

Luo, Wei, Ou, Shiqi(Shawn), Zhou, Pan, Wang, Tianpeng, Qian, Xiaodong

A Large Language Model-Based Database for Analyzing the Electric Vehicle Battery Supply Chain

2026-01-0471To be published on 04/07/2026

Global geopolitical volatility poses a critical threat to the resilience of the electric vehicle battery supply chain. Static, manually updated databases fail to capture the sector's rapid dynamics, creating significant information gaps for strategic planning. This study proposes an Artificial Intelligence-driven methodology to construct a comprehensive and dynamic knowledge base. An automated pipeline is implemented, beginning with specialized web crawlers that harvest real-time textual data from curated news and industry sources. This unstructured data is preprocessed through deduplication and cleansing to ensure quality. The core innovation involves applying fine-tuned Large Language Models (LLMs) to perform deep semantic parsing and extract structured information. These models precisely identify key entities—corporations, facilities, production capacities—and delineate the complex multi-tier relationships from raw material extraction to final distribution. The output is an

Zhu, Juntong, Luo, Wei, Zhang, Xiang, Yang, Zhifeng, Ou, Shiqi(Shawn), He, Xin

Guidelines for Interior Material Selection to Enhance Thermal Safety in Electric Vehicles

2026-01-0249To be published on 04/07/2026

Due to the rapid advancement of electric vehicles, the role of material selection has become very critical for ensuring passenger safety, particularly in mitigating risks associated with Lithium-Ion (Li-Ion) battery thermal runaway. Unlike internal combustion engine (ICE) vehicles, electric vehicles require interior materials that provide superior fire resistance, thermal insulation, and minimal smoke emission to protect vehicle occupants in extreme thermal events. This paper examines the importance of selecting fire-resistant materials, thermally stable polymers, and low-toxicity materials that can slow fire propagation, reduce interior temperatures, and reduce hazardous gas emissions. Through the integrating of materials with high thermal stability, self-extinguishing properties, and heat-reflective coatings, manufacturers can enhance vehicle interior safety, improve passenger protection, and optimize energy efficiency.

El-Sharkawy, Alaa, Taha, Nahla, Asar, Mona, Sheta, Mai

Comparing the Dynamic Response of a Rolling Tire using Data Collected using a 3D Scanning Laser Doppler Vibrometer

2026-01-0592To be published on 04/07/2026

Detailed tire response data is necessary to advance vehicle safety, and monitor real time tire health. This study presents a non-contact experimental method to measure the vibratory characteristics of a tire subject to shaker excitation and road rolling forces. A Global Electric Motorcars (GEM) E4 electric vehicle was mounted on a chassis dynamometer to simulate loading conditions in a controlled environment. Scanning laser vibrometry (SLDV) was employed to capture out of plane velocity responses across the tire surface using a three independent laser configuration. This technique enables visualization of mode shapes under static and dynamic excitation. The results from SLDV identified the tire’s dominant resonant frequencies and corresponding operating deflection shapes under both static and dynamic conditions at different velocities. The dynamic measurements revealed that the harmonics of rotational frequency dominated higher order structural responses. Incorporating a reference

Gower, Adam, Baqersad, Javad, Gupta, Arjun

Improving Winter Driving Range of EVs with a Novel Desiccant Device: Ceramic Humidity Regulator (CHR)

2026-01-0117To be published on 04/07/2026

With Rapid growth of Electric Vehicles (EVs) in the market, challenges such as driving range, charging infrastructure, and reducing charging time needs to be addressed. Unlike traditional Internal combustion vehicles, EVs have limited heating sources and primarily uses electricity from the running battery, which reduces driving range. Additionally, during winter operation, it is necessary to prevent window fogging to ensure better visibility, which requires introducing cold outside air into the cabin. This significantly increases the energy consumption for heating and the driving range can be reduced to half of the normal range. This study introduces the Ceramic Humidity Regulator (CHR), a compact and energy-efficient device developed to address driving range improvement. The CHR uses a desiccant system to dehumidify the cabin, which can prevent window fogging without introducing cold outside air, thereby reducing heating energy consumption. CHR is based on desiccant dehumidification

Sakai, Naoki, Takahiko, Nakatani, Shinoda, Narimasa, Ihara, Yukio, Wakida, Norihiro, Kato, Kyohei, Anoop, Reghunathan-Nair

A Real-Time Repositioning Strategy for SAEV Fleets Using a Simulation-Informed Deep Learning Model

2026-01-0035To be published on 04/07/2026

Shared Autonomous Electric Vehicles (SAEVs) can enhance urban mobility and efficiency. However, their operational performance is often hindered by the spatio-temporal imbalance between vehicle supply and passenger demand, leading to long wait times. This paper develops a novel repositioning framework where a lightweight CNN, informed by computationally intensive multi-agent simulations, enables real-time strategy deployment. The results show that: (1) An optimized repositioning policy, calibrated via multi-agent simulation, effectively cuts the mean passenger waiting time from 12.0 to 3.0 minutes (a 75% reduction). (2) A lightweight CNN surrogate model enables real-time deployment, reducing the policy computation time from ~4 hours to ~5 minutes (>98% faster). (3) The deep learning surrogate achieves this speed with a negligible performance trade-off, increasing the waiting time by only 0.156 minutes (4.9%) compared to the full optimization.

Shang, Kai, Wang, Ning

The Impact of Extreme Ambient Temperatures on Electric Vehicle Performance in the Kingdom of Saudi Arabia

2026-01-0133To be published on 04/07/2026

The rapid expansion of Saudi Arabia’s electric vehicle sector driven by manufacturers such as CEER Lucid Tesla and BYD necessitates evaluating vehicle performance under extreme thermal conditions. This study investigates the impact of high ambient temperatures on electric vehicle operation by analyzing a 60 kWh NMC battery pack under representative Riyadh summer conditions of up to 47 °C using MATLAB Simulink simulations. The results show that elevated temperatures accelerate state of charge (SOC) depletion and increase battery internal resistance. To maintain safe operating limits the BTMS must operate continuously consuming up to 20 percent of the available energy. Cooling demand increases nonlinearly with temperature exceeding 40 kW at 50 °C which leads to significant parasitic losses and a 15 to 20 percent reduction in driving range. At the system level this increased energy demand raises charging frequency and intensifies electricity load during peak summer periods thereby

Bedywi, Lama Mohammed A, AlJuhani, Haneen, Duan, Chen, AbdulNour, Bashar

Simulation of Conjugate Heat Transfer using the Lattice Boltzmann Method

2026-01-0135To be published on 04/07/2026

Flow simulation with conjugate heat transfer, which involves fluid flow, conduction, and radiation in solid components, is a critical capability that helps engineers design and evaluate cooling systems for heat-generating components such as brakes, powertrains, batteries, and power electronics for both gasoline and electric vehicles. For this study, we utilize PowerFLOW™, featuring its novel native thermal solver, which models both fluid and solid domains within a single model. For the flow domain, we use the Lattice Boltzmann Method with VLES turbulence modeling based on the RNG k-epsilon method. And for the solid domain, the finite volume method with second-order accuracy for thermal conduction and a surface-to-surface radiation for the surfaces. This approach not only leads to a more integrated and streamlined workflow but also enables an accurate modeling of conduction and radiation. In this study, we demonstrate the accuracy of the conjugate heat transfer simulation methodology

Mukutmoni, Devadatta, Shock, Richard, Li, Han, Wanderer, John

StreamPETR-TKD: Temporal Knowledge Distillation for Efficient 3D Object Detection in Object-Centric Streaming Models

2026-01-0023To be published on 04/07/2026

Bird's-Eye-View (BEV) perception has become pivotal in autonomous driving for 3D object detection, enabling the transformation of multi-view image features into a unified BEV representation. However, purely visual methods still struggle with depth estimation and temporal consistency, particularly in modeling long-term dependencies and avoiding trajectory confusion in dynamic scenes. Knowledge distillation (KD) offers a promising solution by transferring rich knowledge from a powerful teacher model to a efficient student model, enhancing performance without incurring significant computational overhead. This paper aims to enhance the temporal reasoning and geometric understanding of the StreamPETR model—an object-centric, streaming-based 3D detector—via a multi-level distillation strategy. 1.Temporal Relation Distillation: The self-attention mechanisms of the teacher model are distilled to impart temporal relational knowledge, enabling the student to associate object states across time

Yan, Yixiong

Adaptive Torque Vector Control for Distributed Drive Intelligent Electric Vehicles Using Model and Data Driven Approaches

2026-01-0628To be published on 04/07/2026

To effectively improve the performance of chassis control of distributed drive intelligent electric vehicles (EVs) under difference road conditions, especially in combing road information and chassis control for improving road handling and ride comfort, is a challenging task for the distributed drive intelligent EVs. Simultaneously, inaccurate chassis control and uncertainty with system input, are always existing, e.g., varying road input or control parameters. Due to the higher fatality rate caused by variable factors, how to precisely chose and enforce the reasonable chassis control strategy of distributed drive intelligent EVs become a hot topic in both academia and industry. To issue the above mentioned, an adaptive torque vector hierarchical controller based on road roughness and adhesion is proposed, which optimizes the comprehensive performance of vehicle chassis. First, combined with the characteristic of the unbalance dynamic force caused by the air gap between the stator and

Wang, Zhenfeng, Zhao, Gaoming, Zhang, Zhijie

Energy-Efficient Predictive Cruise Control in Heavy-Duty Electric Trucks with Optimization of the Penalty Factor as a Function of Payload

2026-01-0042To be published on 04/07/2026

Heavy-duty Class 8 battery electric trucks not only offer a significant reduction in greenhouse gas (GHG) emissions compared to conventional diesel trucks but can also provide significant savings in fuel costs. To further enhance the energy and freight efficiency, Predictive Cruise Control (PCC) algorithms can be developed that generate optimal acceleration profiles for the vehicle by minimizing a cost function which combines both energy consumption and deviation from the desired velocity. A critical component of the cost function is the penalty factor, which governs the trade-off between energy use and travel time, which are two conflicting objectives in freight logistics. Selecting an appropriate penalty factor is essential, as freight deliveries are time-sensitive but minimizing energy consumption remains a priority. Moreover, variations in payload significantly affect vehicle dynamics and energy usage, making it critical to adapt the penalty factor to different payload conditions

Safder, Ahmad Hussain, Villani, Manfredi, Wang, Eric, Khuntia, Satvik, Nelson, James, Meijer, Maarten, Ahmed, Qadeer

Embedded Real-Time Control of a Distributed Trailer Propulsion System with Regenerative Braking for Net Neutral Load Towing

2026-01-0065To be published on 04/07/2026

Towing significantly degrades vehicle efficiency, reducing battery-electric vehicle (BEV) range by up to 50% and increasing internal-combustion engine (ICE) fuel consumption by ~30%. To address this challenge, this paper presents a real-time embedded control architecture for a distributed trailer propulsion system that actively regulates drawbar force to achieve net neutral load towing while enabling regenerative braking. Unlike prior e-trailer concepts, this platform demonstrates a cost-effective, fully networked, model-based control implementation using commercial off-the-shelf components. The control system integrates dual Raspberry Pi controllers running ROS 2: one samples a hitch-mounted load cell at 100 Hz and the other processes OBD-II/CAN messages. Controllers designed in MATLAB/Simulink are deployed to a 5 kWh LiFePO₄ pack and a 5 kW traction motor, utilising embedded Linux for real-time scheduling and onboard data logging. Two operating modes are implemented: (i) PI

Joshi, Gaurav, Adelman, Ian, Liu, Jun, Donnaway, Ruthie

Methodology to Quantify the Petroleum Equivalent Fuel Economy Impact of BEV Thermal System Energy Consumption

2026-01-0132To be published on 04/07/2026

This paper will present research and 1D modeling results to support a proposed methodology to determine a fleet ambient weighted average Petroleum Equivalent Fuel Economy (PEFE) for the energy consumed by the thermal system of a BEV, including a proposal of how factor in the thermal system PEFE result into an OEM’s overall CAFE determination on an incentivized (not punitive) basis, within the existing regulatory framework. The topic is particularly important because EPA and NHTSA final rules issued in early 2024 eliminated A/C Efficiency Credits for BEVs that are currently in place for all classes of light duty vehicles. However, without some sort of regulatory incentivization, market forces will dictate thermal comfort system solutions that consume more energy – and with that more negative secondary effects such as higher greenhouse gas emissions and vehicle mass - than would otherwise be the case. Eliminating incentivization for BEVs is particularly concerning because the thermal

Taylor, Dwayne

Optimization of a Feedforward Neural Network Machine Learning Battery Model for an Automotive Pouch Cell

2026-01-0386To be published on 04/07/2026

Modern battery management systems have a critical need for highly accurate battery terminal voltage models, which are a key component of algorithms which estimate or predict power capability, range, temperature, and other factors. While electro-chemical and equivalent circuit models are widely used for this purpose, they typically struggle to capture the complex, non-linear dynamics and degradation effects inherent in real-world battery operation, necessitating frequent recalibration. This study addresses these limitations by proposing a robust, data-driven approach for terminal voltage estimation using a feedforward neural network (FNN) machine learning model. An LG E66 cell, a high-performance lithium-ion battery with a Nickel Cobalt Manganese (NCM) cathode, was selected for this study due to its prevalent use in light duty electric vehicles. Data collected at temperatures ranging from 40 °C to -20 °C is used to train and test the models, with model error reported for HWFET, UDDS

Dehury, Biswanath, Nahidmobarakeh, Lucas, Panchal, Satyam, Gross, Oliver, Kollmeyer, Phillip

Novel SOH Estimation Using the Differential Force Signal for Li-ion Batteries under Constraint Conditions

2026-01-0388To be published on 04/07/2026

Accurate estimation of the State of Health (SOH) is crucial for ensuring the safety and reliability of lithium-ion batteries. Compared to conventional electrical signals, battery swelling behavior offers significant advantages as it contains richer aging-related information. This study investigates the aging characteristics of batteries under external mechanical constraints, and proposes an innovative SOH estimation method based on differential force (DFDV) analysis. Cycling tests were conducted on fully constrained LFP prismatic batteries under 0.2 MPa. Throughout the testing, both mechanical and electrical signals were synchronously monitored and recorded. The research systematically analyzes the swelling behavior and aging patterns of batteries. Through incremental capacity analysis (ICA), the aging behavior and underlying mechanisms under room-temperature and constrained conditions were revealed. Simultaneously, mechanical signal analysis demonstrated a strong correlation between

Niu, Zhice, ZHANG, Shan, Xia, Yong

Methods of Highly Repeatable Lubricant Testing for Electric Vehicles: Universal Motor Control and Statistical Test-Variation Analysis

2026-01-0421To be published on 04/07/2026

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

Luo, Yilun, Gross, Michael, Kostan, Travis

Lightweight Bubble Sheet Panel To Reduce Inverter Noise and Vibration for Electric Vehicles

2026-01-0442To be published on 04/07/2026

Inverters are typically integrated into electric drive units for electric vehicles (EVs) to reduce packaging size and cost. However, coupled vibrations from the electric motor and gears are transmitted to the inverter, which, due to its large radiative panel, becomes a dominant noise source. Metal panels are required for electromagnetic interference (EMI) compliance, yet these covers usually lack sufficient stiffness or damping for noise control. Adding ribs and applying damping treatments results in excessive mass, cost, and packaging challenges. A new, patented bubble sheet panel design has been developed to enhance the structural strength and damping of the inverter while significantly reducing its mass. A thin sheet of aluminum or magnesium is welded onto the cover in an optimized pattern that enhances stiffness and damping performance while accommodating packaging requirements. The welding pattern can include logos or artistic designs to improve the panel’s appearance. The metal

He, Song, Bobel, Andrew, Naismith, Gregory, Yi, Wenwen, Patruni, Pavan Kumar

Identifying pressure drop and heat transfer correlations for a liquid-cooled lithium-ion battery pack model of electric vehicles under hot-cold driving

2026-01-0394To be published on 04/07/2026

The performance of a full lithium-ion battery (LIB) pack with its cooling system depends on the pressure drop and heat transfer from the cell to ambient air through coolant, cooling flow channels, air gaps, and pack cases. Predicting the LIB pack responses (i.e: voltage, SOC, temperature) requires accurate predictions of the thermal performance between the cells and ambient air and cooling flow behaviour inside the pack, respectively, since the pack has several thousand cells, cooling channels, and channel pipe bends. This work presents a systematic approach to identifying heat transfer and pressure drop ∆P correlations that capture the real-time thermal-electrical performance of a mass-produced LIB pack under constant speed (in winter) and transient driving (in summer). A vehicle test is conducted using a Tesla Model Y, a long-range, dual-motor model equipped with a 75-kWh LIB pack. The LIB pack's thermal and electrical performance is recorded under both constant speed and transient

Sok, Ratnak, Kusaka, Jin

Ambient and Initial Temperature Effects on Battery Electric Vehicle (BEV) Range and Energy Consumption Rate Modeled in FASTSim

2026-01-0277To be published on 04/07/2026

Ambient and initial temperatures have a significant impact on the energy consumption rate of battery electric vehicles (BEVs) due to auxiliary loads and the dependence of battery efficiency on temperature. Quantifying these impacts can help BEV owners, communities, and researchers understand and prepare for the impact of temperature on BEV vehicles, especially as adoption increases. We used NREL's FASTSim 3 to investigate the impacts of a two-dimensional design-of-experiment that swept ambient and initial temperature in simulating a compact BEV hatchback over UDDS (city) and HWFET (highway) US EPA drive cycles. Compared to a 22 ° C ("cozy") initial / ambient temperature baseline in UDDS, a cold initial / cold ambient temperature (-7 ° C) resulted in a 221% increase in the energy consumption rate, a cozy initial / cold ambient temperature resulted in a 94% increase, a hot initial (45 ° C) / hot ambient (40 ° C) temperature resulted in a 40% increase, and a cozy initial / hot ambient

Baker, Chad, Steuteville, Robin, Holden, Jake, Gonder, Jeffrey, Carow, Kyle

Dual-loop voltage control of electric vehicle DWPT systems based on robust right coprime factorization and deep Q-networks

2026-01-0208To be published on 04/07/2026

This paper proposes an adaptive robust voltage-control framework for dynamic wireless power transfer (DWPT) systems, explicitly targeting the problem of voltage stabilization under time-varying and uncertain load resistance typical in vehicular charging scenarios. The proposed architecture adopts a dual-loop structure: an inner loop that enforces provable stability via operator-theoretic robust right coprime factorization, and an outer loop that provides high-precision tracking through a data-driven deep reinforcement learning policy. In the inner-loop design, the receiver-side BUCK converter within an LCC-S DWPT topology is modeled in operator form and decomposed into right coprime factors. A controlled operator representation that accounts for unknown disturbances is formulated, and nonlinear control operators are synthesized based on the Bézout identity together with Lipschitz-type conditions. This design ensures bounded-input–bounded-output (BIBO) stability of the inner closed loop

Chen PhD, Jingjun, Zhang PhD, Yizhe, Dai, Yunlong, Wang PhD, Xingyu, Wu, Guangqiang

Quantifying the Impact of Towing on BEV Energy Use: Instrumented On Road Testing and Chassis Dynamometer Reproduction

2026-01-0431To be published on 04/07/2026

Electrification is rapidly entering all vehicle classes, including light- and heavy-duty trucks designed for heavy towing capabilities. Still, the quantitative impact of towing on battery-electric vehicle (BEV) energy use and range remains under-characterized. We conducted controlled towing tests with a Ford F-150 Lightning using two trailers of different sizes and varying payloads to isolate aerodynamic and mass effects across the vehicle’s rated towing capacity. The vehicle was instrumented at the CAN bus level to capture motor power, torque, speed, and other related internal signals. On-road testing consisted of repeated back-and-forth passes on level, straight road segments at set speeds focusing on highway operation, where aerodynamic drag is stronger and real-world towing use cases occur. From these data, we extracted road load equations and dynamometer coefficients for each trailer combination, then reproduced equivalent conditions on a four-wheel drive chassis dynamometer

Timermans Ladero, Inigo

Electric Vehicles & the Grid - Synergy or Strain?

2026-01-0398To be published on 04/07/2026

As the demand for electrical power has surged over recent years due to the increasing popularity of data centers for Artificial Intelligence (AI) and Electric Vehicles (EVs), it is becoming evident that the aging electrical grid infrastructure is struggling to keep up. Some of the problems this aging infrastructure has resulted in include frequent blackouts due to weather related events, reduced efficiency resulting in higher maintenance costs and outdated communication systems causing poor monitoring and response times. Modernization of the grid in conjunction with integration of the transportation sector with the grid is essential to ensure the reliability and resiliency of the grid. Electric vehicles have dramatically increased in popularity, with most vehicle manufacturers offering at least one electric option in their lineups. Looking at recent developments in vehicle-to-grid (V2G) technology, a new possibility becomes evident; instead of straining the power grid, the electric

Dahlmann, Alexander Drake, Lele, Sneha

ZSI Impedance Source inverter integrated XFC ( Extreme fast charging ) for Electric Vehicle

2026-01-0438To be published on 04/07/2026

This paper presents the application of an inverter named Improved Enhanced-Boost Quasi-Z-Source Inverter in AC-connected extreme fast charging (XFC) stations for electric vehicles (EVs), with the goal of reducing conversion stages and enhancing system efficiency. Currently, XFC stations are a focus of development due to their potential to match the refueling time of traditional fuel stations. AC-connected systems offer greater reliability for XFCs compared to DC-connected systems as they tend to have better fault tolerance and are less sensitive to power fluctuations. However, this increased reliability comes at the cost of greater complexity due to the need for multiple conversion stages—such as AC to DC and DC to the required voltage—making the overall system more intricate and potentially less efficient than DC-connected counterparts. The Improved Enhanced-Boost Quasi-Z-Source Inverter addresses this challenge by consolidating the DC-DC and DC-AC conversion stages into a single

SAILESH, DILEEP, Sanaboyina, Prudhvi, Chhagar, Rohnitsingh, Satyanarayan, Swapna

Predicting Electric Vehicle Interior Noise Quality from Drive Unit End-of-Line Vibration Testing

2026-01-0223To be published on 04/07/2026

The Noise, Vibration, and Harshness (NVH) quality of electric vehicles (EVs) is heavily influenced by the performance of the electric drive unit. As a critical step in production, End-of-Line (EOL) testing of drive units is used to assess and control component-level NVH before vehicle assembly. However, the correlation between EOL test results and final vehicle interior noise quality, which directly impacts customer satisfaction, is not always fully understood. This paper presents a methodology for characterizing and predicting vehicle interior noise quality based on data from drive unit EOL vibration testing. Our study investigates the intricate relationship between drive unit assembly variations, component tolerances, and the resulting vibrational response. We establish a robust correlation between these drive unit characteristics and both objective vehicle interior noise levels and subjective customer perception. The findings provide a framework for using EOL data to proactively

Arvanitis, Anastasios, Jangid, Kuldeep

Planning Charging Infrastructure for Electric Freight Corridors

2026-01-0469To be published on 04/07/2026

With the rapid development of electric vehicles, electric freight transportation is gradually increasing. However, the construction of charging infrastructure on expressways has lagged far behind, becoming a key bottleneck in the development of new energy freight transportation. This paper proposes an optimization system for the layout of charging stations in the rest areas of the Beijing–Hong Kong–Macao Expressway, based on freight logistics information. The system combines the Flow Capturing Location-Allocation Model (FCLM) with an improved genetic algorithm to dynamically analyze traffic flow, service area distribution, and charging demand, thereby achieving an optimized layout of charging stations. By simulating traffic flow variations under different scenarios, the study analyzes the spatiotemporal distribution of charging demand and optimizes the selection of charging station sites and charger allocation. Experimental results demonstrate that the proposed optimization method

Guo, Haifeng, Zhang, Jingzhong, Lian, Jintao

Development of a virtual test rig to evaluate thermal management of a battery-electric vehicle under battery heating-cooling modes

2026-01-0416To be published on 04/07/2026

A battery-electric vehicle (BEV) has multiple powertrain components (battery, inverter, e-motor), a thermal management system (compressor, heat exchanger, cabin heating, ventilation, and air-conditioning), and a vehicle body, among others. Vehicle testing is time-consuming, and also changing powertrain components during the testing and design process is costly. Simulation models (aka virtual or simulation test rig) have been widely used for efficient vehicle design. This work presents a systematic approach to developing a virtual test rig to evaluate the thermal performance of battery-electric vehicles. A Tesla Model Y is tested in a chassis dynamometer, and the measured vehicle performance data are used as boundary conditions for the complete vehicle model. The detailed lithium-ion battery (LIB) pack model, including its cooling system, was developed and calibrated using various transient driving cycle data. The HVAC model uses a simplified controller to maintain the cabin temperature

Sok, Ratnak, Kusaka, Jin

Simulation-based prediction and optimization of acoustic comfort in vehicle interiors

2026-01-0502To be published on 04/07/2026

Passenger expectations for quiet and acoustically comfortable vehicle interiors have increased significantly, driven by advancements in electric vehicles and premium audio systems. Acoustic comfort affects perceived quality, communication ease, and overall driving experience. This paper presents a simulation-driven methodology to predict and optimize interior noise performance during the early design phase, focusing on high-frequency acoustic transfer functions and trim material absorption properties. Traditional NVH development relies heavily on physical testing, which is time-consuming and costly. Early-stage predictive tools are essential to evaluate acoustic performance before prototype availability. High-frequency noise (1kHz–12kHz) is particularly challenging due to complex reflections and absorption behavior. Acoustic trims play a critical role in shaping the cabin’s sound field, and their properties must be optimized to achieve desired sound quality. A novel simulation approach

Baladhandapani, Dhanasekar, Jadhav, Vishal, Du, Isaac

Thermal Performance of Natural Fiber Hybrid Composites for Automotive Insulation Applications

2026-01-0244To be published on 04/07/2026

This study investigates the thermal conductivity of natural-fiber-based hybrid polymer composites with potential automotive insulation applications. With the increasing demand for lightweight, sustainable, and thermally efficient materials in vehicle cabins, under-hood systems, and electric vehicle battery enclosures, natural fiber composites present a promising alternative to conventional glass-fiber composites. Three distinct composite configurations were fabricated: pure glass, glass-jute hybrid, and glass-jute-coir hybrid, using general-purpose polyester resin as the matrix. The composites were manufactured using the hand lay-up method. Thermal conductivity measurements were conducted using the ASTM C177 guarded hotplate method on composite plates. Results indicate that the hybrid composite with glass, jute, and coir fibres has the lowest thermal conductivity, making it the most effective for insulation applications. This study demonstrates that natural fibre-reinforced composites

Mache, Ashok, Salve, Aniket, Chinchanikar, Satish, Borse, Hardik, Deshmukh, Omkar, Mahadikpatil, Siddhi, Kulkarni, Aparna

Thermal Characterization of an Automotive High Voltage Junction Box

2026-01-0390To be published on 04/07/2026

The high voltage battery junction box (HVJB) controls and protects the high voltage connections of the battery pack to the traction, auxiliary and charging systems. HVJBs are composed of busbars, contactors, fuses and other protection systems. The health of the HVJB is paramount to ensure performance and reliability of electric vehicles. However sensing and monitoring in the HVJB is often lacking due to cost, causing limited capability of the vehicle controller to estimate the status and health of the unit. This publication focuses on the experimentation of an automotive HVJB to characterize the operation and build the foundation for the development of prognostic algorithms for HVJB. A production HVJB has been acquired and heavily instrumented. Extensive testing are performed in adiabatic and in ambient conditions at various current levels for various durations of operation. The testing setup was calibrated and iterated based on preliminary results, and the testing conditions were

Arigo, Sam, Borgerson, Joe, D'Arpino, Matilde, ZHU, Di, Zhang, Liwen

Mechanical Properties of Elastomeric Foam-Based Compression Pads for Battery Pack Applications

2026-01-0247To be published on 04/07/2026

With the increasing adoption of electric vehicles (EVs) worldwide, ensuring the long-term reliability and performance of the battery systems has become a paramount engineering challenge. Lithium-ion cells exhibit dimensional changes throughout their operational life, characterized by reversible “breathing”—expansion and contraction during charge and discharge cycles—and irreversible swelling due to aging. Compression pads are critical components for ensuring the lifetime performance of battery packs. The primary function of a compression pad is to act as a compliant cushion between cells. It accommodates these volumetric fluctuations by exerting consistent and optimized pressure. By absorbing the stress from cell expansion and maintaining structural integrity within the module, compression pads mitigate degradation mechanisms and ultimately maximize the durability and safety of the battery system over thousands of cycles. This paper highlights the importance of tailoring elastomeric

Deng, Weilin, Gunashekar, Subhashini

Physical Test Validated Multi-level Power Electronics for Next-generation Electrified Vehicles Charging & Efficiency Improvement

2026-01-0435To be published on 04/07/2026

Improving the energy efficiency of electrified vehicles remains a central objective in modern electric powertrains. Multi-level converters (MLCs) are widely recognised for lowering conversion losses relative to two-level inverters and improving total harmonic distortion (THD) in the sinusoidal supply to motors with a consequent reduction in motor losses. Despite this, sustained production-oriented validation at the integrated system level remains limited. This work introduces a multi-level converter architecture of the Battery Integrated Modular Multi-Level Converter (BIMMC) topology using Cascaded H-Bridge (CHB) architecture. It offers improvements in all key metrics of performance, cost, package size, mass and robustness compared to the current state-of-the-art two-level inverter system with distributed functions for charging available in the market today. The overall solution is highly functionally integrated. It supports four major functions required in electric vehicles without

Bao, Ran, Kalaiselvan, Prashanth, Rener, Kristof, Hallam, Philip, Shi PhD, Kai, Yue, William, Ma, He, Grimshaw, Andrew, Patel, Simon

Propulsion System Design Considerations for HEV versus EV Applications

2026-01-0641To be published on 04/07/2026

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

Momen, Faizul, Jensen, William, Das, Shuvajit, Chowdhury, Mazharul, Alam, Khorshed, Anwar, Mohammad, Reinhart, Timothy

Advancing Sustainable Electric Vehicles: A Simulation-Driven Study on Rare Earth-Free Motors and Battery Technologies

2026-01-0242To be published on 04/07/2026

As electric vehicles (EVs) become more popular, the growing dependence on rare earth materials in their motors and batteries has raised concerns about supply risks, environmental impact, and rising costs. Finding alternatives to these materials is essential to making EVs more sustainable and affordable for everyone. This study aims to explore new motor designs and battery chemistries that reduce or eliminate the use of rare earth elements. We will focus on promising options like induction and wound rotor motors, as well as ferrite and iron-nitride magnets that can replace traditional rare earth magnets in EVs. On the battery side, we will look at lithium-iron-phosphate (LFP) and sodium-ion batteries, which offer a safer and more cost-effective alternative while maintaining good performance. A big part of this work involves using advanced simulations to predict how these new materials and designs will perform. This lets us optimize the components before building physical prototypes

Saraswat, Shubham, Vishe, Prashant

Development of the Honda S+ Shift Utilizing e:HEV System

2026-01-0418To be published on 04/07/2026

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

Murata, Naoya, Narimoto, Ryosuke, Saito, Masatoshi, Ishida, Daichi, GUNJI, HIROKI, UKAI, YOHEI, Kurachi, Shinobu, SHIKI, KAZUKI, Nagakura, Akari, Maeda, Sadaharu, Mitogawa, Terumasa

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