Browse Topic: On-board vehicle charging systems

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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
An Adaptive Brake Force Allocation Strategy for Rear-Wheel Driven EVs2026-01-06364/7/2026
Due to changed requirements compared to conventional propulsion concepts, electromobility demands new and innovative strategies for energy-efficient vehicle motion control. For example, the challenge in purely rear-wheel drive (RWD) electric vehicles (EVs) is to achieve a maximum of regenerative braking power in order to increase energy recovery and to ensure, that this does not impair the braking stability. Within this conflict between energy efficiency and braking dynamics, it is necessary to design an intelligent strategy to optimise recuperation. This paper presents such a strategy, which improves an existing approach formerly presented by the authors, but specifically optimised to overcome weaknesses. The previous approach had two major limitations: First, the efficiency map of the in-wheel machines (IWMs) was not considered. Second, there was no possibility of switching flexibly between different brake force distributions to guarantee both, maximized recovery potential and high braking stability, in fulfilment of legislative requirements. The new strategy addresses these shortcomings by introducing a speed-dependent torque limit for the electric drive motors to avoid inefficient operating and uses two independent factors to manipulate the brake force distribution along the axles and vary the distribution between the actuators. In addition, various scenarios were analysed and incorporated into the new strategy in order to achieve optimal torque distribution in every driving situation. The developed approach was implemented into a real vehicle and extensively tested in driving trials on closed-off terrain and on public roads. The results of the investigation demonstrate the ability to ensure stable vehicle control and a 45.3 % increase in energy recovery in comparison to the established benchmark.
Mitsching, Thomas, Heydrich, Marius, Ivanov, Valentin
Characterizing Regenerative Braking of the Tesla Model 3 Using Chassis Dynamometer Testing2026-01-04534/7/2026
Regenerative braking has a strong influence on the energy efficiency and drivability of battery-electric vehicles. This study establishes an empirical baseline analysis under controlled conditions of the regenerative braking behavior of the 2020 Tesla Model 3 to support the interpretation of on-road performance and serve as a reference for subsequent testing and analysis. The tests were performed on a four-wheel-drive chassis dynamometer at Argonne National Laboratory, combining Multi Cycle Testing (MCT) to simulate real world driving patterns (city, highway) with coast-down tests to isolate periods where the motor is operating in regen mode and compare the behavior across different parameters. Vehicle data was collected from the vehicle using taps in the Controller Area Network (CAN) bus as well as a high-resolution power analyzer. The vehicle displayed the highest efficiency during simulated city driving conditions (3.62 miles/kWh followed by highway (3.40 miles/kWh) and aggressive (2.53 miles/kWh) conditions, though aggressive driving showed the highest energy recovery. Regenerative energy recovery was most efficient in the 10 – 30 mph range, with the rear motor regenerating all the energy while the front motor used a small amount of power. Standard regen mode achieved 57% greater deceleration during coast down compared to Low Regen mode and showed a much lower variability during different simulated uphill and downhill conditions. Standard mode collected more energy than Low mode in all cases apart from simulated downhill tests where Low mode performed better. These results provide an overview of the Tesla Model 3 regenerative braking behavior and delineate operating regimes that maximize efficiency and quantify trade-offs between deceleration stability and energy recovery across driver-selectable modes. The results provide a rigorous, reproducible baseline and measurement protocol that can enable cross-vehicle benchmarking, validate vehicle/software-in-the-loop models, and inform future controller calibration and the design of on-road and track experiments
Pierce, Benjamin Branch, Di Russo, Miriam, Das, Debashis, Zhan, Lu, Stutenberg, Kevin
Backlash Evasion Strategy for Enhancing Vehicle Cornering Performance2026-01-06404/7/2026
This study presents a torque distribution control strategy for EVs with e4WD powertrain to overcome the trade-off between ensuring vehicle acceleration and deceleration responsiveness and mitigating backlash shock in the driving system. The deterioration of the drivability which occurs from the intrinsic hardware characteristics of the drivetrain is prevented by designing a response-priority drive mode in which neither front or rear motor torque is allowed to change its sign. Instead, in such drive mode, the front motor torque is only allowed to perform regenerative braking while the rear motor torque is only allowed to produce positive acceleration torque. In order to avoid sacrificing the maximum acceleration by applying such strategy, the mode transition function is implemented as well. In addition, in order to prevent backlash impact due to drivetrain compliance, variable offset torque based on drivetrain compliance model is evaluated in real time and applied to each motor command generation strategy. The enhancement of vehicle drivetrain responsiveness directly leads to improved track driving performance, particularly for the neutral-balance phase during harsh cornering. The effectiveness of the suggested driveline torque distribution method is verified using an actual vehicle driven on the race track, and the vehicle responsiveness followed by track driving performance indices are numerically assessed for comparison.
Oh, JIWON, Lee, Ho Wook
Quantifying the Impact of Towing on BEV Energy Use: Instrumented On Road Testing and Chassis Dynamometer Reproduction2026-01-04314/7/2026
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 and to span the full range of towable payloads within the vehicle’s rated capacity. The vehicle was instrumented at the CAN bus level, capturing motor power, torque, speed, and related internal signals from different control modules. 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 across several standard cycles. Results were consistent across runs, showing a significant increase in the vehicle’s overall energy consumption and a corresponding range penalty. Additional impacts on vehicle systems due to towing, including thermal management of the motors and battery, were quantified. Dynamometer tests of varying characteristics (highway, urban, steady state speeds and accelerations) allow isolation of specific behaviors in functions like regenerative braking operation and torque-split strategy. Dynamometer results aligned with on-road measurements, enabling repeatable laboratory evaluation of towing scenarios. These findings provide a validated methodology and dataset to quantify towing impacts on BEVs, inform range prediction and route planning, support labeling and consumer guidance, and characterize sustained, high load real world operation of vehicle components.
Timermans Ladero, Inigo
Embedded Real-Time Control of a Distributed Trailer Propulsion System with Regenerative Braking for Net Neutral Load Towing2026-01-00654/7/2026
Towing imposes substantial efficiency penalties on both battery-electric vehicles (BEVs) and internal combustion engine (ICE) vehicles, reducing range by 30-50%. This paper presents a proof-of-concept embedded control architecture for distributed trailer propulsion that actively regulates drawbar force to reduce towing loads. Unlike proprietary e-trailer systems requiring specialized hardware, the proposed implementation demonstrates feasibility using commercial off-the-shelf (COTS) components and open-source software. The distributed architecture employs dual Raspberry Pi 4B single-board computers communicating via ROS 2 at 20 Hz. The trailer-mounted controller executes a Simulink-generated control node coordinating load cell acquisition (HX711 ADC), motor CAN bus telemetry, and throttle commands to a 5 kW BLDC traction motor powered by a 5 kWh LiFePO4 battery pack. A vehicle-mounted controller logs OBD-II/CAN validation data. The control pipeline implements cascaded EWMA/Hampel digital filtering with intentional phase lag for hitch-force regulation. The system was validated through on-road testing with an ICE towing vehicle pulling a 1,000-lb trailer over standardized 2.1 km segments following SAE J1321 Type II procedures. Preliminary trials demonstrated stable control performance with drawbar force regulation with no oscillatory behavior. Fuel consumption measurements showed promising improvements (9.4% lower fuel consumption in assisted vs. baseline conditions), though limited sample size precludes definitive causal claims. The primary contribution is establishing technical feasibility of cost-effective COTS implementation (USD 5,000 hardware cost) for trailer propulsion control, providing a foundation for expanded validation studies and commercial deployment pathways.
Joshi, Gaurav, Adelman, Ian, Liu, Jun, Donnaway, Ruthie
Control Strategy Optimization to Improve Energy Efficiency of Electric Wheel Loader Wheel Drive System02-19-02-00113/27/2026
Driven by the dual-carbon goals of “peak carbon emissions” and “carbon neutrality,” improving energy efficiency in electric construction machinery has become a key focus. This study proposes an energy-saving torque control strategy for the traction motor of electric wheel loaders, aiming to reduce drive system energy consumption. The innovation lies in coupling parameter optimization of the pedal–torque mapping and regenerative braking to enhance overall efficiency. An electric model was built using Cruise and validated against real-world V-cycle test data, showing good agreement with an average relative error of 4.08%. Based on the model, two optimized control strategies were developed and evaluated through simulations and field tests. The results showed energy savings of 7.08% and 16.18% in simulation, and 6.83% and 15.51% in tests, respectively, demonstrating the effectiveness and practical value of the proposed method.
Ming, Qiaohong, Wang, Yangyang, Wang, Feng
Regenerative Braking Control Strategy for Electric Commercial Bus under Indian Road Condition Using Artificial Neural Network2026-26-06451/16/2026
The main focus of this paper is to create a more efficient regenerative braking control strategy for electric commercial buses operating under Indian road conditions. The strategy uses Artificial Neural Networks (ANNs) to optimize regenerative braking process. Regenerative braking helps to recover energy that would otherwise be lost during braking and convert it back into usable power for the vehicle. The challenge is to design a system that works effectively on the diverse and often challenging road conditions found in India, such as varying gradients, traffic patterns, and road surface types. This study begins by collecting data (which includes vehicle speed, traffic condition, etc.) from real-world driving conditions and aims to train an Artificial Neural Network (ANN) using a large set of driving data which is collected under various conditions to predict the most efficient regenerative braking settings for different driving scenarios. This research brings a new approach to the application of regenerative braking in electric buses by using Artificial Neural Networks. Previous works in this area mostly focused on passenger vehicles or did not take into account the unique challenges posed by Indian road conditions, such as heavy traffic and frequent elevation changes. This study addresses those challenges directly by focusing on electric buses, which are a growing segment of the public transportation sector in India.
Saurabh, Saurabh, Bhardwaj, Rohit, Patil, Nikhil, Gadve, Dhananjay, Amancharla, Naga Chaithanya
Multi-Physics Simulation and Reliability Analysis of Onboard EV Charger2026-26-04991/16/2026
The rapid advancement of electric vehicle (EV) technology has created a demand for reliable and Thermal - efficient electronic components for power electronics and control systems on printed circuit boards (PCBs). The research looks at the overall simulation and study of a PCB for Electric Vehicles, including how it handles heat, stress, and reliability in real working conditions like considering casing (Heat Sink) in which PCB is held, into the simulation. We have used numerical based methods (reliability), Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) methods to simulate heat performance looking at steady-state and changing load profiles common in EV powertrains. We ran structural and thermal simulations to check the PCB's toughness against heat expansion and shaking loads often seen in cars. We also did a reliability check looking at heat cycling life for PCB components, and possible ways it could break to guess long-term toughness. The results show critical hot spots in the PCB design, structure warping from mechanical stress, and highlighted key things that affect how long the PCB components can lasts. Based on these simulations, we suggested some ways to manage heat, and structural rigidity, like selecting better materials and placing parts at smarter location. This study shows a step-by-step way to use multi-physics simulations early when designing EV PCBs leading to better heat control mechanical toughness, and overall system reliability.
Kanbarkar, Suraj Omana, Deore, Uday, Patil, Nishikant, Nayak, Shibabrata
Scalable and Modular Data-Driven Hybrid Chassis Dynamometer Framework for EV Powertrain Evaluation2026-26-03631/16/2026
In its conventional form, dynamometers typically provide a fixed architecture for measuring torque, speed, and power, with their scope primarily centered on these parameters and only limited emphasis on capturing aggregated real-time performance factors such as battery load and energy flow across the diverse range of emerging electric vehicle (EV) powertrain architectures. The objective of this work is to develop a valid, appropriate, scalable modular test framework that combines a real-time virtual twin of a compact physical dynamometer with world leading real-time mechanical and energy parameters/attributes useful for its virtual validation, as well as the evaluation of other unknown parameters that respectively span iterations of hybrid and electric vehicle configurations, ultimately allowing the assessment of multiple chassis without having to modify the physical testing facility's test bench. This integration enables a blended approach, using a live data source for now, providing a point of calibration and validation for the virtual model(s), as well as using the virtual model capability to determine other unknown/measurable characteristics about the physical model. So, this test framework makes that system's capability, representing an enhancement to its ability, with a virtual twin merging them together to enable virtual evaluation of multiple configurations of the chassis without changing the physical test stand. So, this combined real-world and virtual framework offers a scalable and flexible testing and modelling platform for both early performance characterisation, as well as life cycle-based energy evaluations. In responding to the identified gaps, this work introduces an innovative hybrid chassis dynamometer framework that applies to a real-world test bench in tandem with a concurrently simulated virtual model, offering early-stage validation and optimisation potential using the shift-left development proposition. The result is a reusable and forward-thinking platform supporting efficient EV development by forecasting and drawing informed insights into energy flow, battery performance, and lifecycle behaviour from ahead of typical physical testing boundaries.
Kumar, Akhilesh, V, Yashvati
Enhancing Range Prediction Accuracy for the BEV: Bridging the Gap between Simulation and Real-World Testing2026-26-05211/16/2026
Accurate range estimation in battery electric vehicles (BEVs) is essential for optimizing performance, energy efficiency, and customer expectations. This study investigates the discrepancies between physical test data and simulation predictions for the BEV model. A detailed range delta analysis identifies key contributors to the observed deviations, including regenerative braking inefficiencies, increased propulsion demand, auxiliary loads, and estimated drivetrain losses within the Electric Drive Module (EDM) during traction and regen. Results indicate that the test vehicle exhibits lower regenerative braking efficiency, higher traction forces and lower regen energy than predicted by simulations, primarily due to EDM inefficiencies and friction brake usage during regeneration. The study underscores the importance of refining simulation methodologies by integrating real-world, test based EDM loss maps to improve accuracy and better align predictive models with actual vehicle performance. Future work will focus on enhancing simulation fidelity and minimizing range estimation deviations to support BEV development and validation.
Mahajan, Prasad, Kesarkar, Sidhesh, Ali, Shoaib
Predictive SoC Management for Enhanced Recuperation Efficiency in Electric Vehicles2026-26-01541/16/2026
In recent years, the automotive industry has been looking into alternatives for conventional vehicles to promote a sustainable transportation future having a lesser carbon footprint. Electric Vehicles (EV) are a promising choice as they produce zero tail pipe emissions. However, even with the demand for EVs increasing, the charging infrastructure is still a concern, which leads to range anxiety. This necessitates the judicious use of battery charge and reduce the energy wastage occurring at any point. In EVs, regenerative braking is an additional option which helps in recuperating the battery energy during vehicle deceleration. The amount of energy recuperated mainly depends on the current State of Charge (SoC) of the battery and the battery temperature. Typically, the amount of recuperable energy reduces as the current SoC moves closer to 100%. Once this limit is reached, the excess energy available for recuperation is discharged through the brake resistor/pads. This paper proposes a method to minimize the energy wastage due to the SoC constraints by predicting an optimal start SoC. The optimal SoC is calculated in such a way that it maximizes energy recovery during regeneration while taking the route attributes, weather conditions, and charger availability into account. On a hilly route, it was noticed that the recuperated energy was 5 times more while using the optimal SoC, compared to the 100% start SoC. This reduction in SoC prevents overcharging and contributes to lesser charging time. Consequently, this approach would positively impact overall battery health, energy efficiency, and contribute to promoting sustainability.
Barik, Madhusmita, S, Sethuraman, Aruljothi, Sathishkumar
Optimization of Inverter Control Strategies for Improved Powertrain Efficiency Using E-Motor Emulation Platforms2026-26-05091/16/2026
As the brain and the core of the electric powertrain, the traction inverter is an essential part of electric vehicles (EVs). It controls the power conversion from DC to AC between the electric motor and the high-voltage battery to enable effective propulsion and regenerative braking. Strong and scalable inverter testing solutions are becoming more essential as EV adoption rises, particularly in developing nations like India. In India, traditional testing techniques that use actual batteries and e-motors present several difficulties, such as significant safety hazards, inadequate infrastructure, expensive battery prices, and a shortage of prototype-grade parts. This paper presents a comprehensive approach for traction inverter validation using the AVL Inverter TS™ system incorporating an advanced Power Hardware-in-the-Loop (PHiL) test system based on e-motor emulation technology. It enables safe, efficient, and reliable testing eradicating the need for actual batteries or mechanical loads. Testing across signal and power levels and the validation of both inverter hardware and software under real-world driving scenarios can be facilitated with proposed test system. Indian OEM challenges like reduction in battery development costs, ensuring high replication precision, and managing thermal and power instability in early-stage prototypes are primary focus areas for this test system. With the Inverter TS, various motor types (IM, EESM, PMSM), switching strategies, and SiC based 800V architectures with different control architectures can be emulated and validated, which can further be optimized for powertrain efficiency. Inverter efficiency maps can be derived and fast control strategy can be iterated which facilitates the the overall drivetrain optimization. This paper focus on how adopting such emulation test methodologies can help EV developers to overcome infrastructure gaps, reduce time-to-market, and enhance powertrain efficiency at a lower cost.
Mehrotra, Soumya, Chhabra, Rishabh
Simulation Research on Torque Vectoring, Braking, Chassis Control Strategies for Electric & Hybrid Vehicles using System Simulation2026-26-04231/16/2026
Electric Vehicles and Plug-in Hybrids alleviate the energy crisis but pose a unique challenge for vehicle dynamics. Though significant developments in motor control strategy and energy density management are evolving, we face significant challenges in torque management, with several ADAS features being an integral part of the EVs/xHEVs. It demands high-fidelity physical and control model exchanges between electric chassis, ride-handling, tire modelling, steering assist, powertrain, and validation using a 0D–1D platform. This paper explicates a unified strategy for improving overall vehicle performance by intelligently distributing and coordinating drive torque to enhance traction, stability, and drivability across diverse operating conditions through co-simulation. The co-simulation platform includes physical models in AMESIM, and control strategies integrated in MATLAB/Simulink. The platform features comprehensive representations of digital vehicles that require detailed modelling of the electric motor, transmission, differential, suspension, wheel dynamics, resistive forces (aerodynamic drag, rolling resistance), and road gradient effects, enabling accurate emulation of real-world vehicle behavior. Correlation of test vs. simulation validates the functionality and robustness of the interaction between physical, basic, and application software control strategy. Digital vehicle validation includes traction-based torque limitation (Correlation: >90%), distributing proportionate hydraulic and regenerative braking to improve braking performance, one-pedal driving and stoppage (Correlation: > 85%), SOC influence on regenerative braking, and smooth torque vectoring during dynamic behavior. Evaluation of diverse driving scenarios like, Gradient profiles (Uphill/Downhill/Curvilinear banking), Gradient-μ surfaces for real-world road profiles extracted from GPX/OSM data. Outcome of correlation details reduction of torque fluctuation, vehicle jerk during mode switching & stoppage, Anti-rollback, Aggressive Acceleration, Failure mode mimicking inverter failure in E-powertrain to construct a dynamic target to avoid lateral deviation.
Eruva, Patrickxavier, Sarapalli Ramachandran, Raghuveeran, Chougule, Sourabh, Natanamani-Pillai, Siva Subramanian, Scheider, Clement, Leclerc, Cedric, Natarajasundaram, Balasubramanian
Research on Low-Power Control of Offshore Wind Sail Stabilization Devices Based on Single Pendulum Control Simulation2025-99-013111/11/2025
To tackle persistent operational instability and excessive energy consumption in marine observation platforms under wave-induced disturbances, this paper introduces a novel ultra-low-power stabilization system based on pendulum dynamics. The system employs an innovative mechanical configuration to deliberately decouple the rotation axis from the center of mass, creating controlled dynamic asymmetry. In this behavior, the fixed axis serves as a virtual suspension pivot while the camera payload functions as a concentrated mass block. This configuration generates intrinsic gravitational restoring torque, enabling passive disturbance attenuation. And its passive foundation is synergistically integrated with an actively controlled brushless DC motor system. During platform oscillation, embedded algorithms detect angular motion reversals. In addition, their detection triggers an instantaneous transition from motor drive to regenerative braking mode, and transition facilitates bidirectional electromechanical energy conversion. Experimental validation under simulated marine conditions demonstrates steady-state attitude stability with minimaldeviation under consistent low power consumption during constant wave exposure. Meanwhile, the system effectively handles dynamic wave spectrum transitions requiring real-time swing parameter adjustments. The adjustments involve significant angular displacements with varying temporal dynamics. Accommodation is achieved through autonomous power reallocation, enabling rapid stability recovery within a fraction of an operational cycle. Concurrently, consistently high energy regeneration efficiency is maintained across most of the operational envelope (85-97%). These capabilities substantiate the dual achievement of exceptional disturbance rejection in harsh marine environments and ultra-low power operation. This establishes a technically viable paradigm for next-generation energy-autonomous stabilization platforms.
Zhang, Tianlin, Liu, Shixuan, Xu, Yuzhe
Research on Methods for Quantitative Assessment of Vehicle Controllability Level2025-99-010111/11/2025
As one of the main indexes of functional safety evaluation, controllability is of critical significance. According to ISO26262 standard, by analyzing the impact of potential faults such as unexpected torque and regenerative braking force loss on vehicle controllability under different working conditions, this paper designs a vehicle controllability test scheme under abnormal motor function under multiple scenarios such as straights, lane changes and curves, and builds a test scheme under abnormal motor function. The mapping relationship between vehicle dynamic state data and controllability level provides a new idea for quantitative analysis of vehicle controllability.
Yang, Xuezhu, He, Lei, Li, Chao, Ren, Zhiqiang
Power Electronics: The Backbone of Sustainable Electrification2025-28-022811/6/2025
Power electronics are fundamental to sustainable electrification, enhancing energy, efficiency, integrating renewable energy sources, and reducing carbon emissions. In electric vehicles (EVs), power electronics is crucial for efficient energy conversion, management, and distribution. Key components like inverters, rectifiers, and DC-DC converters optimize power from renewable sources to meet EV system requirements. In EVs, power electronics convert energy from the lithium-ion battery to the electric vehicle motor, with sufficient propulsion and regenerative braking. Inverters is used to transfer DC power from the lithium-ion eEV battery to alternating current for the motor, while DC-DC converters manage voltage levels for various vehicle systems. These components maximize EV energy efficiency, reduce energy losses, and extend driving range. Power electronics also support fast and efficient battery charging, critical for widespread EV adoption. Advanced charging solutions enable rapid charging times and connecting with renewable energy sources, enhancing transportation sustainability. Vehicle to grid (V2G) capabilities allow Electric vehicles to act as storage devices, providing grid support and contributing to energy stability. Key components in EVs include wide band semiconductors like Silicon Carbide and Gallium Nitride, which offer superior efficiency, higher temperature tolerance, and better thermal management compared to current silicon semiconductors. These materials are effective in high-power applications and revolutionize power electronics technologies. In summary, power electronics is necessary for integrating renewable energy, electrifying transportation, and optimizing energy use in EVs. Its impact drives the transition to a low-carbon future and supports the sustainability of modern transportation systems.
Pipaliya, Akash Pravinbhai, Hatkar, Chetan
Evaluation of Alternative Cooling Method for High Performance Resistors in Zero-Emission Trucks2025-28-035910/30/2025
High Performance Resistors (HPR), also known as brake resistors are used in zero emission vehicles (ZEVs) to dissipate excess electrical energy produced during regenerative braking, as heat energy. It is necessary to use a suitable cooling technique to release this heat energy into the atmosphere in a regulated manner. Currently in most of the ZEVs, liquid cooled HPR with its dedicated heat exchanger and other auxiliaries such as pump, surge tank, Coolant and coolant lines, is used which increases the cost, packaging space and assembly time. This paper presents air cooling as a substitute heat-exchanging technique for high-performance resistors which eliminates the need of auxiliaries mentioned above, resulting in space optimization and reduction in assembly time. An air cooled HPR, designed for this study consists of a heat exchanger, which accommodates a resistor wire within its tubes. The design was made to fit commercial vehicle use, specific to trucks, due to packaging constraints in vehicle under hood. 1D simulation model made with MATLAB Simulink was used to analyse this design's heat rejection capabilities. The results conclude that for sufficient air flow rate, air cooled HPR can be used as an alternative in trucks.
Menariya, Pravin Ganesh, Kumar, Vishnu, Arhanth, Mahima, Umesha, Sathwik, Jagadish, Harshitha
Optimal Control Strategy for Dual-Motor EVs with CVT: Comparison of Simulation of Steady-State and Dynamic Programming Methods2025-01-040710/7/2025
This study investigates an optimal control strategy for a battery electric vehicle (BEV) equipped with a high-speed motor and a continuously variable transmission (CVT). The proposed dual-motor powertrain model activates only one motor at a time, with Motor A routed through a CVT and Motor B through a fixed gear. To improve energy efficiency, two optimization methods are evaluated: a quasi-steady-state map-based approach and a dynamic programming (DP) method. The DP approach applies Bellman’s principle to derive the globally optimal CVT ratio and motor torque trajectory over the WLTC cycle. Simulation results demonstrate that the DP method significantly improves overall efficiency compared to traditional control logic. Furthermore, the study proposes using DP-derived maps to refine practical control strategies, offering a systematic alternative to conventional experimental calibration.
Zhao, Hanqing, Moriyoshi, Yasuo, Kuboyama, Tatsuya
Enhancing Capacitance of High-Rate Electric Double-Layer Capacitors with CO 2 -Activated Mesoporous Carbon Gel Electrodes2025-01-506410/2/2025
Electric double-layer capacitors (EDLCs) store charge by adsorbing ions at the electrode–electrolyte interface, offering fast charge–discharge rates, high power density, minimal heat generation, and long cycle life. These characteristics make EDLCs ideal for memory backup in electronic devices and power assistance in electric and hybrid vehicles, where rapid energy response and high-power delivery are critical. However, their energy density remains lower than that of batteries, requiring improvements in capacitance and operating voltage. Activated carbon with high surface area is commonly used as the electrode material, but its microporous structure limits ion transport at high rates, reducing power performance. This limitation is especially critical in automotive motor drive systems. Recent research has shifted toward mesoporous carbon materials, which improve ion diffusion and accessibility. In this study, resorcinol–formaldehyde carbon cryogels (RFCCs) with controlled mesoporous architectures were synthesized and applied as EDLC electrode materials, in combination with organic electrolytes that provide a wider electrochemical window. A CO2-activated RFCC (RFCC-CO2) demonstrated the most balanced electrochemical performance, combining high surface area and interconnected mesoporous networks. Characterization using scanning electron microscopy (SEM) and Brunauer–Emmett–Teller (BET) surface area analysis confirmed the hierarchical porous structure. Electrochemical evaluations through cyclic voltammetry (CV) and constant current charge–discharge measurements demonstrated that RFCC-CO2 achieved high specific capacitance and excellent rate capability. These results point to the importance of mesopore engineering in addressing ion transport limitations in conventional carbon materials and highlight RFCC-CO2 as a promising electrode candidate for EDLCs in regenerative braking and other fast-response electric mobility applications.
Cheng, Zairan, Okamura, Tsubasa, Ohnishi, Yuto, Nakagawa, Kiyoharu
Enhanced Vehicle Capability Through Innovative High Voltage Power Solutions2025-01-05069/16/2025
Increasing the mission capability of ground combat and tactical vehicles can lead to new concepts of operation that enhance safety and effectiveness of warfighters. High-temperature power electronics enabled by wide-bandgap semiconductors such as silicon carbide can provide the required power density to package new capabilities into space-constrained vehicles and provide features including silent mobility, boost acceleration, regenerative braking, adaptive cooling, and power for future protection systems and command and control (C2) on the move. An architecture using high voltage [1] would best satisfy the ever-increasing power demands to enable defense against unmanned aerial systems (UAS) and offensive directed energy (DE) systems for advanced survivability and lethality capabilities.
Eddins, R., Lambert, C., Habic, D., Haynes, A., Spina, J., Schwartz, E.
A Study on the Development of Optimal Brakes for Electric Vehicles Using Simulation2025-01-03459/15/2025
As the ICE vehicle changes into the EV, we can use regenerative brake. It can improve not only the energy consumption but also reduce the hydraulic brake usage. The less hydraulic brake usage mitigates the heat loading on the brake disc. From this reason, the lightweight brake can be used in the EV. However, when the lightweight brake is applied, the brake NVH can be increased. The optimization design of the lightweight brake should be done to prevent the brake NVH. In this paper, the optimal brake disc thickness and brake interfaces are determined by using of disc heat capacity analysis. The lightweight brake should be optimized by using of the brake squeal analysis. We can verify the results from both analysis and test. Finally, we can have the lightweight brake, which is competitive in terms of cost, weight and robust to the brake NVH.
Kim, Sungho, Kim, Jeongkyu, Hwang, Jaekeun, Kang, Donghoon
Bolstering Driver Braking Confidence – Considerations for “Deceleration Adder” Technologies2025-01-03539/15/2025
Over the life of a typical vehicle (often estimated as 15 years or 300,00 km), an average driver can be expected to apply the brakes about 1.6 million times – almost 9 times per mile and over 290 times per day, and an “exuberant” driver can be expected to do this over 2.2 million times. Without question, the driver becomes accustomed to how the vehicle responds to braking control (and all of the normal variation around it), and even develops expectations for how it will respond the next time the brakes are employed. In the rare event of a failure or malfunction in the brake system resulting in an appreciably different vehicle response to the brake input, this can be surprising and even alarming to the driver, sometimes to the extent of causing hesitation in braking. Fortunately, with the rise of mechatronic braking actuators in the 1980’s and 1990’s paved the way for features such as “Driver Brake Assist” (which provides additional pressure beyond what the primary brake actuator can at the time) and “Panic Brake Assist” (which provides additional pressure beyond what the driver is requesting, when the brake apply rate is above a calibratable threshold) to be developed. These features used the new (at the time) brake actuator, the hydraulic pump in the anti-lock brake unit, to provide additional assist to the driver if needed. Vehicles of today will often have multiple actuators capable of providing deceleration, including a mechatronic (or vacuum) brake booster, regenerative braking, electric parking brake actuators, and in some cases a secondary brake module. With these added degrees of freedom, comes added opportunity to improve performance and therefore the driver’s confidence in the vehicle’s braking capability, but also added complexity. With actuators able to increase - depending on their installation - braking on the front axle, the rear axle, or both, and with the ability to suppress hydraulics via valve control to reduce pedal travel, important considerations for brake balance and vehicle stability arise, which must be balanced with straight line performance and brake feel. The present work briefly examines the history of “deceleration adders” (supplemental brake actuators used to improve performance in certain operating conditions such as system failures), draws from published information to establish a framework for the performance necessary to maintain the driver’s confidence, and discusses different actuator types and control strategies along with considerations for integrating them into the brake system.
Antanaitis, David
An Eco-Charging Strategy for Heavy-Duty Electric Vehicles via Graph Optimization2025-24-01169/7/2025
An optimization framework for trip and charging planning for electric heavy-duty vehicles is proposed in this paper. Building upon and extending previous work on light-duty vehicles, our approach models energy-aware routing by constructing a state-augmented graph that jointly captures geographic position and battery state-of-charge. We refine the route model to include detailed vehicle dynamics and speed constraints specific to heavy-duty vehicles, and introduce an alternative graph construction method that avoids the computational complexity of lexicographic products by generating only feasible nodes. The resulting framework enables efficient trip planning that accounts for driving behavior, road characteristics, and charging infrastructure. Simulation results demonstrate the effectiveness of the approach in reducing energy consumption and ensuring operational feasibility for long-haul freight transport.
Zonetti, Daniele, Sciarretta, Antonio, De Nunzio, Giovanni
Electric Bus NVH Challenges and Refinement Using Innovative Approach2025-01-00805/5/2025
The trend towards electrification propulsion in the automotive industry is highly in demand due to zero-emission and becoming more significant across the world. Battery electric vehicles have lower overall noise as compared to conventional I.C Engine counterparts due to the absence of engine combustion and mechanical noise. However, other narrowband and tonal noises are becoming dominant and are strongly perceived inside the cabin. With the ongoing push towards electrification, there is likely to be increased focus on the noise impact of gearing required for the transmission of power from the electric motor to the road. Direct coupling of E-motors with Axle has resulted in severe tonal noises from the driveline due to instant e-motor torque ramp up from 0 rpm and reverse torque on driving axle during regenerative braking. The tonal noises from the rear axle during vehicle running become very critical for customer perception. For automotive NVH engineers, it has become a challenge to balance expected noise performance and manufacturing limitations of hypoid gears for rear axles and transmissions in case they are carried forward from existing designs used for ICE configurations. In this paper, the challenges and refinement strategy for driveline NVH issues in a battery electric bus were discussed. The study found that in-cabin noise was unacceptable in both the speed sweep and coasting down between 35-40 km/hr and beyond 50 km/hr speed. Transfer path analysis, operational deflection shape analysis, modal analysis, and order analysis methodologies were adopted to identify the source of noise. The analysis revealed the effect of gear macro and micro geometry on rear axle whine, and the occurrence of resonance frequencies during both speed sweep and coast down. The torsion resonances as well as other subsystem resonances were also getting coupled in the same problematic frequency bands. To improve the NVH, both source and transfer path refinement opportunities were explored. Hypoid gear macro & micro geometry optimized to improve contact ratio & minimize transmission error. The driveline modes were decoupled using propeller shaft stiffness optimization, Inertia ring on the propeller shaft, modal decoupling using mass and torsional dampers, and improvements in attachment stiffness. When all design modifications were assessed on the electric bus, the overall noise level in the problematic speed zone was reduced by around 8-10 dB (A) in speed-sweep as well as coasting down. The electric bus with all feasible solutions was presented to juries, and the subjective rating was improved to 'Fair'.
Doshi, Sohin, Kalsule, Dhanaji, Sawangikar, Pradeep, Suresh, Vineeth, Sharma, Manish
Power Quality Requirements for Plug-in Electric Vehicle ChargersJ2894/1_202504 (Current)4/14/2025
The intent of this document is to develop a recommended practice for PEV chargers, whether onboard or off-board the vehicle, that will enable equipment manufacturers, vehicle manufacturers, electric utilities, and others to make reasonable design decisions regarding power quality. The three main purposes are as follows: 1 To identify those parameters of a PEV battery charger that must be controlled in order to preserve the quality of the AC service. 2 To identify those characteristics of the AC service that may significantly impact the performance of the charger. 3 To identify values for power quality, susceptibility, and power control parameters that are based on current U.S. and international standards. These values should be technically feasible and cost effective to implement into PEV battery chargers. SAE J2894/2 will describe the test methods for the parameters/requirements in this document.
Hybrid - EV Committee
Evaluation and Prevention of Brake Drum Freezing by Aerodynamic Measures2025-01-87754/1/2025
The use of drum brakes in Battery Electric Vehicles (BEVs) offers numerous benefits, including energy efficiency, reduced brake dust emissions, and reliable performance under challenging weather conditions. The capability of regenerative braking reduces the friction brake application frequency in BEVs and therefore the brakes can be prone to corrosion and performance degradation especially considering conventional disc brake systems. The closed design of a drum brake prevents corrosion of the friction-components by sealing out water, dirt or snow. A common sealing concept is performed with a labyrinth between the gap of the rotating drum and the axle mounted backplate. A hermetical isolation of water and snow ingress into the drum cannot be achieved with this concept, so additional aerodynamic measures are necessary to deflect the air/water path and protect the inner brake components. Additionally, interfaces like wheel cylinders, electric park brake parts, brake shoe pins, and axle mountings can potentially lead to leaks on the backplate. This study highlights the impact of water/snow ingress on the example of a frozen parking brake during cold climate on-road testing. Through scientific investigation using the state-of-the-art fluorescence method, drum leakages were visualized, and the extent of water ingress was measured. Multiple multiphase CFD simulations supported the design phase of the aerodynamic measures. Subsequently, the vehicle was cooled down to -10 °C to simulate the cold climate test conditions. The frozen parking brake situation could be reproduced with this method, and beneficial aerodynamic and sealing measures were extrapolated to avoid the drum brake from freezing. The tests were conducted in the FKFS Thermal Wind Tunnel, a wind tunnel comprising a two-axle-dynamometer and water irrigation systems with UV illumination.
Hennicke, Tim, Kuthada, Timo, Bernhard, Adrian, Reichhart, Leander, Weber, Eugen, Moers, Michael, Rettig, Marc
Smart Boosting: A Control Strategy for Optimized Energy Management with Boost Converter in Hybrid Electric Vehicles2025-01-85804/1/2025
In hybrid electric vehicles (HEVs), optimizing energy management and reducing system losses are critical for enhancing overall efficiency and performance. This paper presents a novel control strategy for the boost converter in hybrid electric vehicles (HEVs), aimed at minimizing energy losses and optimizing performance by modulating to a higher boost converter voltage only when necessary. Traditional approaches to boost converter control often lead to unnecessary energy consumption by maintaining higher voltage levels even when not required. In contrast, the proposed strategy dynamically adjusts the converter's operation based on real-time vehicle demands, such as driver input, Engine Start-Stop (ESS) events, Active Electric Motor Damping (AEMD), entry and exit transitions for Engine Fuel Cut-Off (DFCO), Noise-Vibration-Harshness (NVH) events like lash-zone crossing and other specific operational conditions. The control strategy leverages predictive algorithms and real-time monitoring to selectively engage the boost converter, ensuring that it only steps up voltage when the system demands it, thus reducing unnecessary power losses. This approach not only enhances the overall efficiency of the powertrain but also improves the vehicle's responsiveness and drivability by delivering optimal power during critical events like sudden acceleration, regenerative braking, and vibration damping through AEMD. Simulation results and real-world testing demonstrate that this adaptive control strategy significantly reduces energy losses, contributing to extended battery life and improved fuel economy in hybrid electric vehicles. The findings suggest that the implementation of this control strategy can play a vital role in advancing the efficiency and performance of future HEV powertrains.
Basutkar, Ameya, Huo, Shichao, Sullivan, Claire, Berger, Daniel, Tischendorf, Christoph
Bi-Level Control Co-Design for Parallel Electric-Hydraulic Hybrid Vehicles2025-01-85824/1/2025
This study presents a control co-design method that utilizes a bi-level optimization framework for parallel electric-hydraulic hybrid powertrains, specifically targeting heavy-duty vehicles like class 8 semi-trailer trucks. The primary objective is to minimize battery energy consumption, particularly under high torque demand at low speed, thereby extending both battery lifespan and vehicle driving range. The proposed method formulates a bi-level optimization problem to ensure global optimality in hydraulic energy storage sizing and the development of a high-level energy management strategy. Two nested loops are used: the outer loop applies a Genetic Algorithm (GA) to optimize key design parameters such as accumulator volume and pre-charged pressure, while the inner loop leverages Dynamic Programming (DP) to optimize the energy control strategy in an open-loop format without predefined structural constraints. Both loops use a single objective function, i.e. battery energy consumption, to ensure a globally optimal offline solution. Key findings reveal that the Recurrent Neural Network (RNN)-based online energy controller replicates the offline DP solution with near-optimal performance, achieving real-time and closed-loop control with robustness. Furthermore, simulation results demonstrate significant savings in battery energy and overall system efficiency, highlighting the potential of this method for real-world applications.
Taaghi, Amirhossein, Yoon, Yongsoon
Study on Emergency Obstacle Avoidance Lateral Stability Control of Tractor Semitrailer Vehicles2025-01-82964/1/2025
As a crucial component of highway freight systems, tractor semitrailer vehicles play a key role in the transportation industry. However, their complex vehicle structure can lead to significant lateral instability during emergency obstacle avoidance, posing challenges to the vehicle's dynamic stability and safety. To enhance the emergency obstacle avoidance lateral stability of tractor semitrailer vehicles, a direct yaw moment lateral stability control strategy based on differential driving/braking is proposed. First, a 3-degree-of-freedom ideal linear dynamic model of the tractor-semitrailer is established, and its accuracy is validated. Then, a lateral stability control strategy for emergency obstacle avoidance is proposed. The upper-layer controller employs an improved feedforward differential model-free adaptive control (IMFAC) method to track the target yaw rate and vehicle sideslip angle, while the lower-layer controller focuses on optimizing tire load rate. Additionally, a drive/brake torque distributor is introduced to prioritize regenerative braking. The proposed control strategy is validated under simulated DLC conditions representing emergency obstacle avoidance. The results show that the designed controller improves the lateral stability of the tractor-semitrailer by over 30% in DLC scenarios, ensuring accurate trajectory tracking while maintaining low drive wheel tire load rate. This effectively extends the safety margin for tractor-semitrailer obstacle avoidance and provides valuable insights for improving lateral stability during emergency maneuvers.
Guo, Shaozhong, Dou, Jingyang
Refining Control, Charging, and Battery Chemistry for CO 2 e Savings in Heavy-Duty Off-Road Plug-In Series Hybrid14-14-02-00092/27/2025
With current and future regulations continuing to drive reductions in carbon dioxide equivalent (CO2e) emissions in the on-road industry, the off-road industry is also likely to be regulated for fuel and CO2e savings. This work focuses on converting a heavy-duty off-road material handler from a conventional diesel powertrain to a plug-in series hybrid, achieving a 49% fuel reduction and 29% CO2e reduction via simulation. Control strategies were refined for energy savings, including a regenerative braking strategy to increase regenerative braking and a load-following hydraulic strategy to decrease electrical energy consumption. The load-following hydraulic control shuts off the hydraulic electric machine when it is not needed—an approach not previously seen in a load-sensing, pressure-compensated system. These strategies achieved a 24.1% fuel savings, resulting in total savings of 61% in fuel and 41% in CO2e in the plug-in series compared to the conventional machine. Beyond control strategies, this study evaluated battery chemistry and charging strategy refinements for total cost of ownership (TCO) and lifetime CO2e. LFP batteries emerged as the most cost-effective and least emitting due to their longer lifespan, which reduced replacement frequency. Charging comparisons showed that Level 2 charging (L2C) typically resulted in lower TCO but higher lifetime CO2e than DC fast charging (DCFC). DCFC costs were heavily influenced by local demand charges, and DCFC emissions were heavily influenced by local grid emissions.
Goodenough, Bryant, Czarnecki, Alexander, Robinette, Darrell, Worm, Jeremy, Subert, David, Kiefer, Dylan, Heath, Matthew, Brunet, Bob, Kisul, Robert, Latendresse, Phil, Westman, John, Black, Andrew
Optimization-Based Battery Thermal Management for Improved Regenerative Braking in CEP Vehicles2024-01-29747/2/2024
The courier express parcel service industry (CEP industry) has experienced significant changes in the recent years due to increasing parcel volume. At the same time, the electrification of the vehicle fleets poses additional challenges. A major advantage of battery electric CEP vehicles compared to internal combustion engine vehicles is the ability to regenerate the kinetic energy of the vehicle in the frequent deceleration phases during parcel delivery. If the battery is cold, the maximum regenerative power of the powertrain is limited by a reduced chemical reaction rate inside the battery. In general, the maximum charging power of the battery depends on the state of charge and the battery temperature. Due to the low power demand for driving during CEP operation, the battery self-heating is comparably low. Without active conditioning of the battery, potential of regenerating energy is partially lost because the friction brake needs to absorb kinetic energy whenever the cold battery’s limit is exceeded. This paper proposes an optimization-based strategy for the battery thermal management of CEP vehicles. The tradeoff between the cost of battery heating and the benefit of regenerative braking is investigated under cold ambient conditions. For this purpose, a nonlinear model predictive control approach is developed to maximize the overall vehicle efficiency depending on the upcoming driving task by selective battery heating. The evaluation shows that the increase in overall efficiency depends on the electric efficiency of the battery heating system, the ambient conditions, the intensity and frequency of the deceleration phases, and the usage behavior of the vehicle. Based on the assumption that the driving cycle and ambient conditions can be accurately predicted, the model-in-the-loop simulation indicates a reduction in energy consumption of up to 3.3 % with an electric coolant heater and up to 9.6 % with an ambient heat pump.
Rehm, Dominik, Krost, Jonathan, Meywerk, Martin, Czarnetzki, Walter
Control System for Regenerative Braking Efficiency in Electric Vehicles with Electro-Actuated Brakes10-08-02-00155/1/2024
This article presents the design and the analysis of a control logic capable of optimizing vehicle’s energy consumption during a braking maneuver. The idea arose with the purpose of enhancing regeneration and health management in electric vehicles with electro-actuated brakes. Regenerative braking improves energy efficiency and allows a considerable reduction in secondary emissions, but its efficiency is strongly dependent on the state of charge (SoC) of the battery. In the analyzed case, a vehicle equipped with four in-wheel motors (one for each wheel), four electro-actuated brakes, and a battery was considered. The proposed control system can manage and optimize electrical and energy exchanges between the driveline’s components according to the working conditions, monitoring parameters such as SoC of the battery, brake temperature, battery temperature, motor temperature, and acts to optimize the total energy consumption. The solution devised allows first to maximize the effects of regenerative braking when the battery SoC is too high to regenerate efficiently, then to safeguard the condition of the battery for both the battery’s long life and overheating and safeguard the condition of the brakes to prevent their overheating.
Tempone, Giuseppe Pio, de Carvalho Pinheiro, Henrique, Imberti, Giovanni, Carello, Massimiliana
Enhancing Regenerative Energy Capture in Electric Vehicles: Braking Performance through Integral Sliding Mode Control10-08-02-00124/18/2024
This article focuses on the development of an active braking control system tailored for electric vehicles. The essence of this system lies in its ability to regulate the slip coefficient to optimize traction during braking, thereby maximizing energy recuperation. In the context of the simulation on enhancing regenerative energy capture in electric vehicles, the use of integral sliding mode control (ISMC) as an alternative for regulating braking performance can be understood through a comparison of two key output variables in braking control systems: wheel deceleration and wheel slip. Traditionally, wheel deceleration has been a controlled variable in braking systems, and it is still utilized in some anti-lock braking systems (ABS). It can be easily measured using a basic wheel encoder. However, the dynamic performance of wheel deceleration control may suffer when there are rapid changes in the road surface. On the contrary, regulating wheel slip offers high robustness from a dynamic perspective. Despite its robustness, accurately measuring wheel slip poses a challenge as it necessitates estimating the vehicle speed. Nonetheless, despite this challenge, controlling wheel slip remains the most suitable option for designing braking controllers that can adapt to variations in road surface conditions. Therefore, integrating ISMC into the braking system as an alternative enables more effective regulation of wheel slip, enhancing the overall performance and resilience of the braking system, which is particularly crucial in electric vehicles where optimizing regenerative braking is a significant concern. The article explores the theoretical dynamics of electric vehicle braking maneuvers and introduces the concept of an ISMC for managing the slip coefficient. Utilizing a robust control law in conjunction with this controller guarantees the exponential convergence of slip error. Afterward, we explore the visualization and simulation of the braking process performed by the ISMC, as well as the storage of the recovered energy in a supercapacitor system using MATLAB/Simulink.
Direm, Chaima, Hartani, Kada
An Adaptive Clamping Force Control Strategy for Electro-Mechanical Brake System Considering Nonlinear Friction Resistance2024-01-22824/9/2024
The Electronic Mechanical Braking (EMB) system, which offers advantages such as no liquid medium and complete decoupling, can meet the high-quality active braking and high-intensity regenerative braking demands proposed by intelligent vehicles and is considered one of the ideal platforms for future chassis. However, traditional control strategies with fixed clamping force tracking parameters struggle to maintain high-quality braking performance of EMB under variable braking requests, and the nonlinear friction between mechanical components also affects the accuracy of clamping force control. Therefore, this paper presents an adaptive clamping force control strategy for the EMB system, taking into account the resistance of nonlinear friction. First, an EMB model is established as the simulation and control object, which includes the motor model, transmission model, torque balance model, stiffness model, and friction model. Subsequently, a cascaded clamping force controller, consisting of clamping force loop, velocity loop, and current loop, is designed for EMB using Proportional-Integral (PI) control theory. On this basis, fuzzy theory is applied to adaptively adjust the PI control coefficients of the clamping force loop, and an Extended State Observer (ESO) is introduced in the current loop to dynamically estimate and compensate for the friction resistance of the EMB system. Finally, a simulation platform is established using MATLAB/Simulink for testing and validation. Simulation results demonstrate that ESO accurately estimates the friction torque in real-time, and the proposed adaptive clamping force control strategy effectively controls the EMB to overcome non-linear friction resistance, with a clamping force tracking error of less than 2% for an 8Hz sine wave input. Moreover, the controller exhibits good adaptability, maintaining high-quality control performance even after altering the simulated control object's friction characteristics.
Xu, Zelin, Wu, Jian, Bi, Gongyuan, Hou, Jie, Zheng, Wenbo, Li, Lun, Gao, Shang, Chen, Zhicheng
Innovative Zero-Emissions Braking System: Performance Analysis Through a Transient Braking Model2024-01-25534/9/2024
This paper presents the analysis of an innovative braking system as an alternative and environmentally friendly solution to traditional automotive friction brakes. The idea arose from the need to eliminate emissions from the braking system of an electric vehicle: traditional brakes, in fact, produce dust emissions due to the wear of the pads. The innovative solution, called Zero-Emissions Driving System (ZEDS), is a system composed of an electric motor (in-wheel motor) and an innovative brake. The latter has a geometry such that it houses MagnetoRheological Fluid (MRF) inside it, which can change its viscous properties according to the magnetic field passing through it. It is thus an electro-actuated brake, capable of generating a magnetic field passing through the fluid and developing braking torque. A performance analysis obtained by a simulation model built on Matlab Simulink is proposed. The model is able to simulate the transient 1D motion of an electric vehicle equipped with four wheels, each having a ZEDS mounted. It has the ability to simulate a road test, supervise the behavior of the vehicle, monitoring parameters such as the State of charge (SoC) of the battery, the current used by the vehicle's battery, speed, drive torque and the decoupling between the regenerative braking torque and the Magneto-Rheological brakes torque. The primary goal of the model is to verify the capability of the braking system to develop a sufficiently high torque to satisfy safety standards and regulation requests. The study creates also a starting point for thermal analysis of the system.
Tempone, Giuseppe Pio, Imberti, Giovanni, de Carvalho Pinheiro, Henrique, Carello, Massimiliana
Real-Time Deployment Strategies for State of Power Estimation Algorithms2024-01-21984/9/2024
Lithium-ion cells operate under a narrow range of voltage, current, and temperature limits, which requires a battery management system (BMS) to sense, control, and balance the battery pack. The state of power (SOP) estimation is a fundamental algorithm of the BMS. It operates as a dynamic safety limit, preventing rapid ageing and optimizing power delivery. SOP estimation relies on predictive algorithms to determine charge and discharge power limits sustainable within a specified time frame, ensuring the cell design constraints are not violated. This paper explores various approaches for real-time deployment of SOP estimation algorithms for a high-power lithium-ion battery (LIB) with a low-cost microcontroller. The algorithms are based on a root-finding approach and a first-order equivalent circuit model (ECM) of the battery. This paper assesses the practical application of the algorithm with a focus on processor execution time, flash memory and RAM allocation using a processor-in-the-loop (PIL) setup. The case study estimates the maximum power available for regenerative braking at high SOCs and compares predictions with experimental data. More specifically, deployments using single and double-precision floating numbers are compared, alongside different voltage estimation approaches. In addition, the bisection root-finding method is compared to the secant and Brent’s method. The different algorithms tested in this study do not significantly impact memory allocation. In terms of processor load, however, single-precision deployments are significantly more cost-effective than double-precision deployments, with a negligible discrepancy in the predicted output. Finally, the secant root-finding method reduces the execution time by two-thirds while retaining the same level of accuracy when compared to the bisection method.
Schommer, Adriano, Araujo Xavier, Marcelo, Morrey, Denise, Collier, Gordana
Fuzzy Control of Regenerative Braking on Pure Electric Garbage Truck Based on Particle Swarm Optimization2024-01-21454/9/2024
To improve the braking energy recovery rate of pure electric garbage removal vehicles and ensure the braking effect of garbage removal vehicles, a strategy using particle swarm algorithm to optimize the regenerative braking fuzzy control of garbage removal vehicles is proposed. A multi-section front and rear wheel braking force distribution curve is designed considering the braking effect and braking energy recovery. A hierarchical regenerative braking fuzzy control strategy is established based on the braking force and braking intensity required by the vehicle. The first layer is based on the braking force required by the vehicle, based on the front and rear axle braking force distribution plan, and uses fuzzy controllers. Achieve one-time distribution of the front axle braking force; the second layer, according to the magnitude of the braking intensity, divides the braking conditions into light braking, moderate braking and emergency braking, and realizes braking under the three working conditions respectively. Secondary distribution of front axle braking force. Using the driving mileage contribution as the evaluation index and NEDC as the simulation working condition, it is verified that the regenerative braking control strategy can achieve energy recovery. To further improve the braking energy recovery and ensure the vehicle braking effect, the braking effect and braking energy recovery are used as the optimization objective function, the particle swarm algorithm is used to optimize the fuzzy rules, and the optimized fuzzy controller is reloaded into the regenerative braking control Simulation is carried out in the strategy to verify that the designed multi-section front and rear wheel braking force distribution curves and fuzzy rules optimized by particle swarm algorithm can effectively improve regenerative braking energy recovery and improve vehicle driving range, while ensuring braking safety.
Zhang, Yu
Optimal Control Co-Design of a Parallel Electric-Hydraulic Hybrid Vehicle2024-01-21544/9/2024
This paper presents an optimal control co-design framework of a parallel electric-hydraulic hybrid powertrain specifically tailored for heavy-duty vehicles. A pure electric powertrain, comprising a rechargeable lithium-ion battery, a highly efficient electric motor, and a single or double-speed gearbox, has garnered significant attention in the automotive sector due to the increasing demand for clean and efficient mobility. However, the state-of-the-art has demonstrated limited capabilities and has struggled to meet the design requirements of heavy-duty vehicles with high power demands, such as a class 8 semi-trailer truck. This is especially evident in terms of a driving range on one battery charge, battery charging time, and load-carrying capacity. These challenges primarily stem from the low power density of lithium-ion batteries and the low energy conversion efficiency of electric motors at low speeds. To address these issues, a recent development is the electric-hydraulic hybrid powertrain. This system includes a hydro-pneumatic accumulator (i.e. a hydraulic energy storage system) and a hydraulic pump/motor (i.e. a hydraulic-mechanical energy conversion system) in addition to all the components of the electric powertrain. The high-level energy control methods of this hybrid powertrain have been extensively studied. In this work, an optimal control co-design framework involving hardware sizing and high-level energy control for a parallel electric-hydraulic hybrid powertrain is addressed. The objective is to maximize overall energy efficiency using a bi-level optimization method. The outer loop seeks optimal sizes for two energy storage systems: the rechargeable lithium-ion battery capacity and the hydro-pneumatic accumulator volume, determining the maximum electric and hydraulic storable energies. Meanwhile, the inner loop aims for optimal energy control with a set of energy storage system sizes using dynamic programming. Numerical studies demonstrate considerable benefits of the proposed control co-design method by applying it to real-world heavy-duty driving cycles. These benefits include reduced electric energy consumption of the lithium-ion battery, potentially allowing for a smaller battery size. Consequently, this increases load-carrying capacity and subjects the rechargeable battery to milder electric stress, thus extending the lifespan. These improvements are achieved through an aggressive use of hydraulic components during regenerative braking and high torque conditions at low vehicle speeds.
Taaghi, Amirhossein, Yoon, Yongsoon
A Study on Effect of Regenerative Braking on Vehicle Range and Axle Life2024-26-02401/16/2024
This paper aims at analysing the effect of regeneration braking on the amount of energy harnessed during vehicle braking, coasting and its effect on the drive train components like gear, crown wheel pinion, spider gear & bearing etc. Regenerative braking systems (RBS) is an effective method of recovering the kinetic energy of the vehicle during braking condition and using this to recharge the batteries. In Battery Electric Vehicles (BEV), this harnessed energy is used for controlled charging of the high voltage batteries which will help in increasing the vehicle range eventually. Depending on the type of the powertrain architecture, components between motor output to the wheels will vary, i.e., in an e-axle, motor is coupled with a gear box which will be connected with differential and the wheels. Whereas in case of a central drive architecture, motor is coupled with gearbox which is connected with a propeller shaft and then the differential and to the wheels. All the components between motor output to the wheels has to be designed and validated for taking the regenerative torque during braking & coasting.
S, Srivatsa, Pethkar, Shivanand, Ghosh, Sandeep
Regeneration Calibration for Optimum Range and Effective Brakes Performances in eSUV2024-26-01101/16/2024
Regenerative braking is an effective approach for electric vehicles (EVs) to extend their driving range. To enhance the braking performances and regenerative energy, regenerative braking control strategy based on multi objective optimization is explained in this paper. This technical paper would be focusing on extracting optimum Range with effective brake performances without affecting drivability and performances in different drives modes. An extensive research study on public road driving patterns is done to understand the percentage utilization of brakes at various (low-mid-high) speeds as per the customer driving behavior. Multi-Objective optimization function with three vital factors is defined where output generated power, torque smoothness and current smoothness are selected as optimization objective to improve the driving range, braking comfort, and battery lifetime respectively. Braking regeneration maps are calibrated along with optimized foundation brake hardware’s to get the optimum range without affecting the brake performances. Ranges tests are conducted on chassis dynamometer with various drive cycles and optimized calibration showed the improved results on range without affecting the braking and acceleration performance feel.
Kumar, Prabhakar, K, Rajakumar, Krishnan, Nandhakumar, Suhail, Mohammed Thamjeed
Enhancing Electric Vehicle Performance and Battery Life through Flywheel Energy Storage System: Modelling, Simulation, and Analysis2024-26-01361/16/2024
This research paper focuses on the modelling and analysis of a flywheel energy storage system (FESS) specifically designed for electric vehicles (EVs) with a particular emphasis on the flywheel rotor system associated with active magnetic bearings. The methodology used simulation approaches to investigate the dynamics of the flywheel system. The objective of this study is to explore the effects of implementing the flywheel energy storage system on the performance of the EV. The paper presents a comprehensive model of the flywheel energy storage system, considering the mechanical and electrical aspects. The mechanical model accounts for the dynamic behaviors of the flywheel, including parameters such as rotational speed, inertia, and friction. The electrical model describes the interaction between the flywheel and the power electronics, such as the converter and motor/generator. To evaluate the benefits of the flywheel energy storage system, simulations are conducted. Simulation studies analyses the dynamic behaviors of the flywheel system under various operating conditions. The results demonstrate that the integration of a flywheel energy storage system in the EV powertrain has a positive impact on the battery life. By capturing and storing excess energy during regenerative braking and other driving conditions, the flywheel system reduces the load on the battery, leading to fewer charge-discharge cycles and slower battery degradation. This prolongs the overall battery life and reduces the need for frequent battery replacements. The research findings highlight the potential of flywheel energy storage systems as an effective solution for extending the battery life of EVs. By utilizing the flywheel system to manage energy fluctuations and provide additional power during high-demand situations, the strain on the battery is significantly reduced. This contributes to increased reliability, lower maintenance costs, and improved overall performance of EVs.
Akhtar, Juned
Study on Range Improvement Controls and Method for Electric Vehicles2024-26-01321/16/2024
Electric Vehicles are rapidly growing in the market yet various doubts on success of its adaptation were noted all along the globe. On the question part range is one of the major attribute; however, range anxiety has greatly inspired manufacturers to explore new practices to improve. One of the most important components of an electric vehicles (EV) is the battery, which converts chemical energy to electrical energy thereby liberating heat energy as the loss. When this heat energy loss is high, the energy available in the battery for propulsion is reduced significantly. Additionally, with a higher heat loss in the battery, system is prone to failure or reduced mileage. Therefore, controlling/maintaining system temperature under safe usable limits even during harsh conditions is critical. Simple reduction in energy consumption of electrical cooling/heating devices used with regenerative energy techniques can greatly help in range improvement. The intention of this paper is to explore ‘program friendly’ methods to improve electric vehicle range in different ambient conditions. Few of the key benefactors here are regenerative braking, a solar roof and defogging method (used along a course of WLTP cycle followed with a highway drive till the end of state of charge). A generic HVAC system is considered with a climate control function. Although, an enhanced strategy is already implemented for Powertrain, Fan and Pump controls which has been done prior to the suggested methods in this paper. Furthermore, the effect of controls on the system are monitored to diversify and optimize the power requirement. Real World scenarios are replicated in 1-D simulation tool for making a comparison between a normal driving mode and enhanced range gain mode. The observations here depict the study on range improvement controls and methods for analyzing vehicle performance in cold and hot climate specific to an electric passenger car.
MR, Vikram, Pattalwar, Ashutosh, Verma, Mrinal, Bawa, Vikas
Drive GPT – An AI Based Generative Driver Model2024-26-00251/16/2024
Good driving practices, encompassing actions like maintaining smooth acceleration, sustaining a consistent speed, and avoiding aggressive maneuvers, can yield several benefits. These practices enhance energy efficiency, reduce accident risks, and significantly lower maintenance costs. Consequently, the presence of a system capable of providing actionable insights to promote such driving behavior is crucial. Addressing this need, the Drive-GPT model is introduced, representing an AI-based generative pre-trained transformer. Within this study, the transformative potential of deep learning networks, specifically based on transformers, is showcased in capturing the typical driving patterns exhibited by individuals in diverse road, traffic, weather, and vehicle health scenarios. The model's training dataset comprises an extensive 90 million data points from multivariate time series originating from telematics systems in 100 vehicles traversing eight distinct Indian cities over a six-month span. These pre-trained models offer substantial utility for downstream applications, including the computation of driving scores, generation of driving recommendations, and the classification of driving behavior as either proficient or suboptimal. The performance evaluation on test data indicates commendable results, with a coefficient of determination (R-squared) of 0.98 and a root mean square error (RMSE) of 0.0346. Furthermore, a discernible differentiation emerges in terms of energy efficiency and regenerative braking between good and suboptimal driving behaviors. Notably, this differentiation leads to a notable 25% improvement in energy efficiency and an 18% enhancement in regenerative capabilities.
Kumar, Vedant, Jain, Siddhant, Soni, Nimish, Saran, Amitabh
Fault Compensation Control for Regenerative Braking of Distributed Drive Electric Vehicle Based on Hierarchical Control2023-01-706112/20/2023
For distributed drive electric vehicles (DDEV) equipped with an electronic hydraulic braking system (EHB) and four-wheel hub motors, when one or more hub motors have regenerative braking failure, because the braking torque of the four wheels is inconsistent, additional yaw moment will be formed on the vehicle, resulting in the loss of directional stability of the vehicle during braking. If it occurs at high speeds, it will further threaten driving safety. To solve the above problems, a new hierarchical control architecture is established in this paper. Firstly, taking DDEV as the research object, the vehicle dynamics model and EHB braking system model are built. Then, a state observer based on an adaptive Kalman filter is designed in the upper layer to estimate the vehicle’s sideslip angle and yaw rate in real time. In the judgment decision-making layer, the phase plane is used to divide the stability domain boundary of the vehicle, and the quasi-stability tolerance band judges the vehicle’s driving state. Secondly, the lower stability controller is constructed based on the sliding mode control theory. EHB can flexibly distribute hydraulic braking force to compensate for the vehicle’s braking force, offset the additional yaw moment, and maintain the straight line of the vehicle. Finally, experimental verification is carried out in Matlab/ CarSim and hardware-in-the-loop (HIL) platforms. The results show that the proposed method can effectively predict the state and closed-loop stability control of DDEV, and reduce the deviation distance caused by regenerative braking failure, effectively ensuring the vehicle in the event of regenerative braking failure driving safety.
Fang, Ting, Zhao, Linfeng, Hu, Jinfang, Mei, Zhen, Wang, Muyun, Sun, Bin
Applying Ferritic Nitrocarburizing (FNC) in Conjunction with Smart ONC® on GCI Brake Rotors: The New Generation of FNC Rotors to Meet the Euro 7 Standards2023-01-188811/5/2023
As the regulations aiming to limit air pollution become stricter, the battle against non-exhaust emissions known to be harmful to human health and the environment is attracting more focus and extending worldwide. EVs are equipped with a hybrid braking system combining regenerative and hydraulic braking to provide the same performance as traditional vehicles. Whenever the regenerative braking torque is insufficient to give the necessary deceleration rate, the hydraulic and electromechanical braking torque is applied. Thus, the recuperative braking of EVs reduces the need for brakes. As the brakes are not used as often, dust and rust will accumulate and impede their performance, so brake problems can arise from not using them enough. Due to the extra weight of EVs compared to ICEVs, more particulates are released through increased corrosion and friction on the braking system. Grey cast iron brake rotors rust quickly, and excessive corrosion causes heavy damage to the rotor’s surface, which wears down severely, leading to mass loss, irregular vibration, and pedal pulsation when braking. Therefore, one of the most economical measures to effectively reduce particulate emissions (PM) is the application of ferritic nitrocarburizing. However, this approach is still insufficient to reach the desired objectives or address the challenges electric vehicles present. The new generation of FNC rotors developed by Nitrex R&D is not limited to FNC; the focus has shifted towards using Smart ONC®. This exclusive and promising process provides rotors with superior corrosion resistance, allowing them to withstand salt spray exposure for up to 120 hours without any corrosion. This is a tremendous improvement over FNC-treated rotors, which only last for less than 20 hours in the same environment. This paper and presentation will follow up on our contribution from 2022 and present Nitrex’s latest findings and developments.
Nousir, Saadia, Winter, Karl-Michael
Using the XiL Approach for Brake Emission Investigations for Electrified Vehicles2023-01-189111/5/2023
The following paper aims to bring the topics of connected testing and emission measurements together. It is an introduction of connected bench testing with the aim to characterize brake particle emissions with a special focus on the impact of regenerative braking by simulating the real behavior of a premium BEV SUV. Such an approach combines the advantages of a brake dynamometer including an emission testing setup and a HiL setup to allow a much more precise testing of brake particle emissions under the impact of regen braking compared to the current recommendations of the Global Technical Regulation (GTR) on brake particle emissions. It is shown for the very first time, how interactions between the vehicle motion system work. The study includes one physical front brake corner as well as one physical rear brake corner. The regen functionalities are simulated by a real ESC-ECU which is the core of the HiL test setup. The presented results will deal with the simulation accuracy, the interactions between the powertrain and friction brake as well as the impact on brake emissions.
Gramstat, Sebastian, Gramstat, Elizaveta, Hense, Maximilian, Zessinger, Marco
Electro-Hydraulic Composite Braking Control Optimization for Front-Wheel-Driven Electric Vehicles Equipped with Integrated Electro-Hydraulic Braking System2023-01-186411/5/2023
With the development of brake-by-wire technology, electro-hydraulic composite braking technology came into being. This technology distributes the total braking force demand into motor regenerative braking force and hydraulic braking force, and can achieve a high energy recovery rate. The existing composite braking control belongs to single-channel control, i.e., the four wheel braking pressures are always the same, so the hydraulic braking force distribution relationship of the front and rear wheels does not change. For single-axle-driven electric vehicles, the additional regenerative braking force on the driven wheels will destroy the original braking force distribution relationship, resulting in reduced braking efficiency of the driven wheels, which are much easier to lock under poor road adhesion conditions. The integrated Electro-Hydraulic Braking system (iEHB) is the current advanced brake-by-wire system, which can build brake hydraulic pressure by its motor, and independently adjusts the four wheel braking pressures through the solenoid valves. Based on the characteristics of the iEHB, a composite braking control strategy for front-wheel-driven electric vehicles is proposed, which adjusts the braking force distribution relationship dynamically. Firstly, the structure of the iEHB system and the wheel braking pressure control principle are analyzed. Secondly, a composite braking control strategy that adjusts the braking force distribution relationship based on current regenerative braking force and wheel braking pressures is designed. Finally, simulations are carried out with the proposed control strategy and the single-channel composite braking control strategy. The simulation results show that the proposed composite braking control strategy can improve the braking efficiency of the driven wheels and improve the energy recovery rate.
Zhao, Xinyu, Xiong, Lu, Zhuo, Guirong, Shu, Qiang, Zhao, Xuanbai
Simulated LACT Procedure for Predicting Lining Life for Vehicles with Regenerative Braking2023-01-189211/5/2023
The Simulated Los Angeles City Traffic (SLACT) test is a well-established dynamometer test procedure used to evaluate brake noise and lining wear performance under a typical US city driving conditions. This procedure is based on a vehicle test conducted on the roads of Los Angeles, California. Unlike ICE vehicles, in electric vehicles regenerative brakes do a significant amount of the work to stop the vehicle, resulting in less work required from the foundation brakes. This means that the life of a brake pad could significantly increase in electric vehicles. It is possible then to reduce the thickness of the brake pad to improve packaging and cost. However, in situations where regenerative braking is disabled due to a failure or low battery charge level, all the work must be done by the foundation brake with no support from the regenerative braking. Hence, it is crucial to select the optimal brake pad thickness for such scenarios. The SLACT test was designed primarily for ICE vehicles and may not represent the lining life of electric vehicles accurately. As more auto manufacturers have started developing electric vehicles, there is now a need to establish a test procedure that considers regenerative braking for lining life predictions. This paper discusses in detail a modified SLACT test procedure that considers regenerative braking for electric vehicle lining life prediction.
Jayyousi, Wael, Divakaruni, Saikiran
Online Identification of Vehicle Driving Conditions Using Machine-Learned Clusters2023-01-160710/31/2023
Modern electrified vehicles rely on drivers to manually adjust control parameters to modify the vehicle's powertrain, such as regenerative braking strength selection or drive mode selection. However, this reliance on infrequent driver input may lead to a mismatch between the selected powertrain control modifiers and the true driving environment. It is therefore advantageous for an electric vehicle's powertrain controller to make online identifications of the current driving conditions. This paper proposes an online driving condition identification scheme that labels drive cycle intervals collected in real-time based on a clustering model, with the objective of informing adaptive powertrain control strategies. HDBSCAN and K-means clustering models are fitted to a data set of drive cycle intervals representing a full range of characteristic driving conditions. The cluster centroids are recorded and used in a vehicle controller to assign driving condition identification labels to the most recently recorded interval of vehicle data. The accuracy of the driving condition identifications of each model is compared by deploying the online identification scheme on the powertrain controller of an electrified vehicle and performing a real-world drive cycle of known driving conditions. The HDBSCAN clusters resulted in superior online driving condition identifications compared to alternative schemes. The main contribution of this paper is the novel application of clustering in an online identification scheme for use in a real-world embedded vehicle controller. By enabling accurate online identification of driving conditions, this approach can improve the powertrain control strategies of electrified vehicles and enhance the driving experience. Future research can leverage the online identification of driving conditions and explore the use of subsequent adaptive control schemes for reducing energy consumption, enhancing safety, and advancing the development of intelligent transportation systems.
Marrone, John Francis, Kwok, Ian, Fraser, Roydon
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