Browse Topic: Electric vehicles

Items (5,111)
Considering the spatial harmonic and time harmonic excitation of the permanent magnet synchronous motor, and the dynamic meshing excitation of gear pairs, this paper constructs one electromechanical coupling torsional vibration model. The torsional vibration characteristics of the electric drive transmission system in pure electric vehicles are investigated. Key electromechanical parameters are obtained by numerical calculations, and the electromechanical coupling system model is solved using the Runge-Kutta method. Finally, the system dynamic response characteristics at rated speed of 3000 r/min are analyzed. The results indicate that the significant bidirectional coupling exists between the electromagnetic excitation of the motor and the mechanical excitation of the gear transmission system. The current spectrum contains fundamental and harmonic components, along with components of gear meshing frequencies and their modulated sideband characteristics relative to the electrical frequency. The electromagnetic torque spectrum exhibits components of gear meshing frequencies, and gear angular velocity fluctuations are influenced by motor harmonic excitation. Under multi-source excitation, this study reveals the frequency modulation mechanism of torsional vibrations in electromechanical coupling drive systems, providing a theoretical basis for vibration and noise suppression.
Luo, YaouZhao, KaihuaFu, Shengping
SiC-based power devices are favored for high-voltage and high-power applications due to their superior material properties. However, the demand for higher breakdown voltages and improved channel mobility presents significant challenges to the etching process, especially the micro-trenching effect. In this study, etching results from inductively coupled plasma (ICP) have been presents, which focused on using various SF6/O2/Ar gas ratios to eliminate micro-trenching effect. The profile analysis of micro-trench was taken by cross-sectional scanning electron microscopy (SEM). The results demonstrate that micro-trenches primarily originate from the coupling effect between ion multi-reflection from sidewalls and redeposition of etch byproducts. Based on this mechanism, we propose a quasi-Bosch process: a combined polymerization and etching step in oxygen-fluorine-rich plasma deposits polymer on exposed SiC and the mask, while removing it from the structure bottom via ion bombardment to enable etching and passivation; then alternates with a short fluorine-plasma step, which consumes sidewall polymer through ion incidence and prevents SiFxOy charge accumulation, cycle etching gradually deepens the structure without micro-trenches. Different gas ratios and etching time not only change the plasma energy distribution but also affect the temporal synchronization between etching and passivation steps. This approach reduces the special demands on ICP equipment capabilities while achieving superior trench profiles. The optimal etching conditions produced a micro-trench-free SiC structure with a vertical sidewall angle and a surface roughness of less than 1 nm. This methodology and resulting structures significantly advance the manufacturability of high-performance SiC power devices, enabling next-generation applications in electric vehicles and grid infrastructure where device yield and reliability are paramount.
Jiang, WenjingYang, ChengyueTang, YidanZhang, RunzeLiu, Yang
The corner module is an innovative design that combines drive, steering, suspension, and other vehicle structures into a single wheel unit. This achieves a high level of integration for chassis functions. A chassis built on this module can perform more complex movements. Suspension is a key part that decides how the vehicle moves. However, current suspension design approaches lack a systematic methodology for configuration synthesis and analytical verification for the multi-degree-of-freedom (multi-DOF) requirements of the corner module. This study introduces a new method for designing the corner module suspension based on the Position and Orientation Characteristic theory (POC theory). First, the type of suspension DOF is derived from chassis functional requirements by treating the required corner module motion as the target suspension DOF. Then, we decide the number of chains, links, and joints in the mechanism and perform configuration synthesis of suspension mechanism. Next, we combine the selected kinematic pairs and select suspension mechanisms that meet the requirements of suspension DOF. There are two steps of calculation in this process. In this study, the goal is to design a suspension with three links, two loops, and two degrees of freedom. Seven suspension mechanisms with specific loops and components were obtained using the proposed process. Finally, the paper presents the process of mechanism verification. Using the steering link and ground excitation as inputs, theoretical calculations and simulation analysis were conducted to verify that the mechanisms obtained meets the suspension design objectives. This proves that the POC theory-based method for creating multi-DOF suspension is effective.
Kong, WenkaiZhu, WenfengZeng, Zhixuan
With the rapid development of the global economy, issues such as the energy crisis and environmental pollution have become increasingly severe. Owing to their environmental friendliness, structural simplicity, and high energy efficiency, electric vehicles have attracted widespread attention. Electric drive technology serves as the most promising and versatile propulsion solution for battery electric vehicles, hybrid electric vehicles, and fuel cell vehicles. As an advanced mechatronic transmission system, the electric drive axle offers high transmission efficiency, flexible packaging, and ease of digital and active chassis control integration, and has thus been increasingly adopted in modern vehicle architectures. The differential is a key component within the electric drive axle, responsible for regulating the rotational speed difference between the left and right wheels and ensuring balanced torque distribution. It plays a decisive role in vehicle stability and traction performance. This study focuses on the reliability testing methodology for differentials in electric drive axles, primarily including the extraction of reliability test conditions and the feasibility analysis of the proposed testing scheme. Specifically, based on the parameters of a given electric vehicle, a Simulink model of the motor and differential is established, and a complete four-wheel-drive vehicle model is constructed. Through simulation under typical driving conditions, operational data of the rear-drive axle differential are obtained. The collected data are then preprocessed and subjected to dimensionality reduction using Principal Component Analysis. The selected principal components are further analyzed using K-means clustering to construct representative differential reliability test conditions. The limitations of existing testing methods are analyzed based on the simulated results and relevant literature. Finally, a reinforced fatigue testing method for the differential is designed according to the extracted test conditions, and the feasibility of the corresponding test bench is evaluated.
Zheng, HongyuLi, ZiyuWang, DajiangTian, Kai
As the energy density of electric vehicle power batteries continues to increase, efficient and uniform heat dissipation has become critical to their safety and performance. The liquid cooling plate serves as the core component of the battery thermal management system, with its flow channel structure directly impacting heat dissipation efficiency and system energy consumption. Current liquid cooling plate flow channel designs often rely on empirical methods, making it challenging to simultaneously optimize both heat dissipation uniformity and flow resistance performance. This paper focuses on a single lithium battery as the research subject, employing a topology optimization approach to design the liquid cooling plate flow channel structure. Optimization targets include minimizing pressure drop at the inlet/outlet and minimizing temperature difference across the contact surface between the plate and the battery. Under constant inlet cross-sectional dimensions and flow velocity, numerical simulation of fluid heat transfer processes revealed an 11.17% reduction in temperature difference across the contact surface. This enhances lithium battery heat dissipation uniformity while reducing inlet/outlet pressure drop by approximately 10.98%. This approach reduces the system energy consumption of liquid cooling. It enables multi-objective co-optimization design for power battery liquid cooling plate structures. It provides new technical references for the refined design of cooling systems in automotive power battery packs.
Ma, HonghuiZheng, YuqingYang, Minghao
High-Voltage Battery (HVB) protection in lateral pole impact is very important due to severe nature of the impact. Unlike frontal impacts, vehicles have limited range of space and capacity to absorb kinetic energy in lateral side impacts. Nowadays, computer-aided engineering (CAE) using finite element analysis (FEA) is utilized routinely to simulate high-speed crash events of varied type, including side pole impact. These CAE applications focus on the analysis and design of HVB when the vehicle structure is well-developed. CAE methods are time-consuming and are not suited during the pre-program stage when the structure is only in a concept stage and not even a reasonable CAD is available/developed in any sense to use these methods. There is no analytical tool available to understand how to define the characteristics of the structure that surrounds and protects the HVB. The primary motive of this publication is to help with this aspect of vehicle planning/development. Needless to state that this procedure can also be used in planning/developing of internal combustion engine (ICE) and hybrid vehicles, as well. The objective therefore is to develop a simple method/procedure that can give reasonably accurate estimation of the collapse/crush force required for a specified crush space and hence protect the critical components, such as HVB and fuel tank. This analytical method also gives some insight into the optimal use of the upper body (rocker and floor cross-members) and underbody (ladder frame) parts. It was found, for a problem under consideration, optimum kinetic energy to be absorbed by the upper body is 32.5% to avoid intrusion into HVB.
Alavandi, BhimaraddiMidoun, DjamalFrank, Randy
Improving the efficiency of electric vehicle (EV) transmissions can help to extend the driving range of EVs, and the EV oil used in these transmissions plays an important role. In this study, in order to enhance energy efficiency, we examined the effects of lowering viscosity, traction, and friction in EV oil. While friction modifiers (FMs) have been widely used as friction reduction technologies in the field of tribology for many years, we previously developed a new FM that reduces friction in drive units. We found that a combination of lowering viscosity and using the developed FM was effective for better energy efficiency. The oil formulated with the developed FM improved efficiency by approximately +0.8% to +0.9% compared to commercial EV oil. EV oil also requires cooling performance. We assumed that reducing heat generation through friction reduction would improve cooling performance and examined the effect of lowering viscosity, traction, and friction. Consequently, it was found that a combination of lowering traction and applying the developed FM is effective for reduction in parasitic heat losses. We also examined durability, which is an issue when reducing viscosity. The results suggested that the oil formulated with the developed FM had good durability for gears and bearings. Thus, we succeeded in developing an ultra-low-viscosity EV oil that has excellent energy efficiency and high cooling performance.
Nakamura, ToshitakaFuruse, TakashiHasegawa, ShinjiAkahori, ShinyaItou, KimikazuSakurada, SoichiroAkiguchi, Junnosuke
SiC-based power devices are favored for high-voltage and high-power applications due to their superior material properties. However, the demand for higher breakdown voltages and improved channel mobility presents significant challenges to the etching process, especially the micro-trenching effect. In this study, etching results from inductively coupled plasma (ICP) have been presents, which focused on using various SF6/O2/Ar gas ratios to eliminate micro-trenching effect. The profile analysis of micro-trench was taken by cross-sectional scanning electron microscopy (SEM). The results demonstrate that micro-trenches primarily originate from the coupling effect between ion multi-reflection from sidewalls and redeposition of etch byproducts. Based on this mechanism, we propose a quasi-Bosch process: a combined polymerization and etching step in oxygen-fluorine-rich plasma deposits polymer on exposed SiC and the mask, while removing it from the structure bottom via ion bombardment to enable etching and passivation; then alternates with a short fluorine-plasma step, which consumes sidewall polymer through ion incidence and prevents SiFxOy charge accumulation, cycle etching gradually deepens the structure without micro-trenches. Different gas ratios and etching time not only change the plasma energy distribution but also affect the temporal synchronization between etching and passivation steps. This approach reduces the special demands on ICP equipment capabilities while achieving superior trench profiles. The optimal etching conditions produced a micro-trench-free SiC structure with a vertical sidewall angle and a surface roughness of less than 1 nm. This methodology and resulting structures significantly advance the manufacturability of high-performance SiC power devices, enabling next-generation applications in electric vehicles and grid infrastructure where device yield and reliability are paramount.
Zhao, YingfanDong, ShuangSun, XiaoxuChang, XiangpengLiang, YiweiTong, Weiping
In order to reduce flow resistance loss in EV thermal management systems, this research builds a comprehensive computational process. The study used an advanced three-dimensional topology optimization technology integrating detailed fluid flow analysis with an adjoint sensitivity solver. This integrated computational approach helps systematic analysis of the complete design region. Thus, the internal flow channels with high resistance can be rearranged. The optimization target was set to minimize total pressure drop under defined operational parameters in real driving conditions. Through iterative calculation, the study successfully created three flow manifolds with different geometric shapes; each flow channel has its own distinct source of high resistance. The results show that the optimization effect is quite good, compared with the traditional manifold developed based on engineering experience; these optimized designs have reduced the pressure drop by 27%, 41%, and 74%, respectively. Beyond these quantitative pressure reduction data, detailed flow field analysis revealed that the optimized manifolds promote substantially improved hydrodynamic characteristics. The optimized internal channels generate more uniform velocity profiles, effectively diminish spatial velocity variations, and restrain vortex formation and recirculation zones. These useful flow field enhancements collectively contribute to a dramatic reduction in energy dissipation. This improves the thermodynamic efficiency of the thermal management system effectively. In order to conduct a more comprehensive verification, the optimized manifold was evaluated under various non-design operating conditions. These three designs consistently maintained stable performance characteristics and their low resistance properties in operating scenarios different from the original conditions, compared to the original manifold. Its stable performance under variable conditions shows the effectiveness of the topology-optimized methods and shows its broad operational adaptability. This is of great significance for the automotive application field, as the operating conditions in this field are often changing.
Liang, ZhixuanTian, RanYe, XiaokangWei, MingshanSun, XiaoxiaShen, Lili
In conventional braking systems, the kinetic energy of a vehicle is predominantly converted into heat through friction, a thermodynamically inefficient process. This not only causes progressive wear of components but also leads to the release of various materials, including heavy metals and organic compounds. With increasing concern over non-exhaust emissions, the search for innovative solutions becomes imperative. In electrified vehicles (xEVs), regenerative braking emerges as a strategic technology, converting kinetic energy into electrical energy to recharge the battery and extend range. This process not only enhances the vehicle's energy efficiency but also results in reduced frequency and intensity of mechanical brake usage. Consequently, there is a direct reduction in the wear of friction braking components, which translates into a significant mitigation of particulate matter emissions associated with this wear. The optimization of these systems occurs through Cooperative Regenerative Braking (CRB), which intelligently integrates with hydraulic braking. The primary challenge lies in managing the transition between modes to recover maximum energy without compromising safety and driver comfort. This technical paper explores how CRB employs 'torque blending' via advanced ECUs and software to adjust in real-time the proportion of each braking type, aiming for maximum energy recovery in diverse driving scenarios. To verify the effectiveness of this system, practical tests were conducted on a vehicle. The results obtained from these tests were conclusive, demonstrating significant gains in energy efficiency, with an increased battery recharging capacity during decelerations, optimized by the braking system. This improvement in efficiency directly impacts the reduction in the use of the conventional friction brake system and, consequently, a sharp decrease in particulate matter emissions. In this context, the intelligent and cooperative management of regenerative braking is a strategic and fundamental component for building a more sustainable future in vehicular mobility.
Batagini, EmersonRomão, Bruno
In recent years, with the rapid increase in the market penetration of new energy vehicles, safety issues in electric vehicles, particularly those characterized by thermal runaway of power batteries, especially fire incidents caused by mechanical abuse from underbody impacts, have become a major focus of industry attention and social concern. This paper systematically compiles key data from electric vehicle underbody collision incidents, covering core parameters such as impact location, geometric features of obstacles (shape and size), and vehicle speed during accidents. Based on this data, the study further reviews existing underbody scraping evaluation protocols both domestically and internationally, with a focused comparison of the differences in mechanical load and battery pack response between two typical test methods: horizontal underbody scraping and 3° inclined underbody scraping. The findings of this research aim to provide data support for the refinement of relevant evaluation standards and to offer theoretical foundations and practical references for automotive manufacturers in optimizing the design and validation strategies for underbody protection of battery packs.
Wang, QingguiHe, QikeLi, WenboLi, ChunLi, Xiaodong
The driving cycle is the basic model of certification of vehicle fuel consumption and emissions, or calibration of powertrains. Standard regulatory driving cycles, such as WLTC, in general assume flat roads during their generation and fail to take into account the strong effect that road gradients have on vehicle operation and driving energy consumption. Such a shortcoming, then, leads to gross mismatches in adaptability when used for urban environments with typical hilly topography. To solve this problem, in this paper, we proposed a method for building driving cycles that consider the impact of slope with actual driving data. Initially, high-precision onboard data collectors were used to generate a total sum of 21, 350 km of driving data from the Munich area, thus creating a diversified driving data set with details such as vehicle speed, slope, and environmental information. Subsequently, joint probability distributions of “speed-acceleration” and “slope-slope change rate” are proposed by using the Micro-trip Method, and a novel chi-squared test algorithm is used to obtain a higher fidelity of urban driving cycle representative of typical conditions. Results of the driving cycle results show that the driving cycle built was close to the actual kinematics, indicating a deviation of less than 5%, and can capture the average uphill characteristic of 1.7%, which is quite well represented. Finally, in fact, validation of whole vehicle environmental chamber tests further demonstrates that the energy consumption prediction error of the developed driving cycle is just 2.2%, much lower than 19.1% error of WLTC. It highlights the importance of considering slope parameters in improving the accuracy of energy consumption calibration for an EV operating on complex slope terrains. Furthermore, it underscores that converting the real-world driving data into lab-based driving cycles can reduce the cost and time of actual road tests for Chinese companies going to the overseas markets, thereby offering support for the international marketing strategy of a global database.
Tian, LichenJiang, PingGao, WangLiang, YongkaiMa, KunqiYu, Hanzhengnan
Historically, the demand for advanced technology, efficiency, and safety has been a primary driving force in the evolution of commercial vehicles, particularly with respect to braking systems. More recently, the increasing levels of vehicle autonomy and electrification have emerged as irreversible trends, significantly accelerating the development of new functionalities and innovative electrical/electronic [E/E] architectures. These advancements are essentially focused on performance optimization, risk mitigation, and enhanced system reliability through the application of functional safety and cybersecurity standards, thereby shaping the current landscape of braking system design. From an efficiency standpoint, braking systems with higher levels of electronic content, functional integration – included with regenerative braking systems - and harmonization have been developed to improve energy efficiency and support global scalability. Concurrently, new system configurations are continuously being introduced to enhance vehicle safety and advanced driver assistance capabilities, in alignment with evolving regulatory requirements and market expectations. This paper evaluates the impacts of automation and electrification on commercial vehicle pneumatic braking systems, focusing on Anti-lock Braking Systems [ABS], Electronic Braking Systems [EBS] and air management platforms. It provides a technical overview of both architectures, assessing their capabilities to meet modern requirements such as integration with advanced vehicle architecture, regenerative braking for electrified applications, and Advanced Driver-Assistance Systems [ADAS] support. The study details the evolution of air management systems, with emphasis on electrified vehicles, including key functions such as air compressor charge control, Air Processing Unit [APU] desiccant regeneration, and electronic control strategies. Additionally, it examines key drivers of braking system evolution, braking system selection considering ADAS regulatory developments, Net Zero strategies, and automation trends. The paper further evaluates compliance with functional safety and cybersecurity standards and assesses the readiness of both platforms for emerging mobility concepts. Finally, it highlights the risks of deploying higher levels of autonomy in heavy-duty towing vehicles when operating with non- ABS semi-trailers, identifying this as a critical area for further investigation.
Guarenghi, Vinícius MendesNicora, FabioPizzi, Rafael FortunaResende, Angelo Roberto RodriguesPinto, Gustavo Laranjeira
Dual-motor architectures provide additional operating degrees of freedom for electric commercial vehicles (ECVs), but the integration of automated manual transmissions (AMTs) introduces torque discontinuities during gear-related mode transitions. Existing energy management strategies usually focus on steady-state efficiency optimization, while the mechanical feasibility of mode transitions is often considered separately or neglected. To address this issue, this study proposes a topology-aware hierarchical control framework for dual-motor ECVs. The framework combines an offline global efficiency map with an online transition-feasibility arbitration mechanism. In the offline layer, the energy-oriented operating mode and torque split are extracted over the vehicle-speed and wheel-torque domain. In the online layer, a topology-based transition matrix is used to identify mechanically singular mode transitions, and potentially torque-interrupting commands are re-routed through feasible bridge modes. The proposed method embeds powertrain topology constraints into the real-time implementation of an offline optimal map, thereby complementing conventional global optimization methods with transition-feasibility arbitration. Simulation results under the CHTC driving cycle show that the proposed strategy improves torque continuity during mode transitions while retaining most of the energy-saving benefit of the unconstrained efficiency-oriented strategy. Compared with the rule-based strategy, the proposed method reduces SOC-equivalent energy consumption by 10.7%, and recovers 65.5% of the DP-achievable energy-saving potential. Hardware-in-the-Loop (HIL) results further demonstrate that the proposed online arbitration logic can be executed within the controller sampling period.
Song, DafengChen, LexinZeng, XiaohuaNi, Lixin
In an ever-evolving landscape of emission regulations, charging infrastructure, customer demands, fuel/energy costs and decarbonization goals, heavy-duty on-road vehicle manufacturers continue to evaluate alternative powertrain technologies. While most heavy-duty vehicle manufacturers now have battery electric vehicles (BEVs) in their portfolio, significant challenges of charging infrastructure, range anxiety, payload capacity reduction and upfront costs have contributed to their lower adoption rates. Plug-in hybrid electric vehicles (PHEVs) have significant potential of leveraging upcoming BEV infrastructure and component supply chains to reduce operating costs while still maintaining longer range and payload capacity benefits of conventional ICE powertrains. This article applies a model-based approach to evaluate multiple Class 7–8 heavy-duty powertrain configurations. A system-level (1D) model of the conventional diesel ICE-based truck was developed in GT-Suite and validated against on-road test data. Using the diesel ICE model as a baseline, system-level models for different hybrid configurations were adapted, and their powertrain architecture was optimized at the system level. Additionally, an equivalent consumption minimization strategy (ECMS) for energy management was also optimized for each of the hybrid powertrain configurations to maximize fuel efficiency and emission benefits. All the hybrid configurations were then compared against the conventional diesel ICE Class 8 truck in terms of performance (acceleration, top speed, gradeability and startability), fuel economy (real-world cycles and certification cycles), emissions, and range for long-haul applications. Unique to this approach is the simultaneous co-optimization of powertrain component sizing and supervisory control logic by utilizing a Genetic Algorithm–based optimization approach. Results indicate that all parallel hybrid architectures (P2, P2–P3, and P4) achieve performance (acceleration, top speed, gradeability, and startability) parity or improvement compared to baseline diesel architecture. P2-based architectures demonstrated a 12–14% improvement in fuel economy on representative real-world cycles when operating in a blended charge-depleting–charge-sustaining mode of operation, and a 4–6% improvement in fuel economy when operating in charge-sustaining mode alone. By quantifying these results across diverse topologies, this work addresses a significant research gap in the holistic evaluation of Class 8 hybrids, specifically, the trade-off between multi-speed electric drives, system-level mass increases, and real-world fuel economy, that remains underexplored in current literature.
Baburaj, AdithyaPaul, SumitDhanraj, FnuJoshi, SatyumFranke, Michael
This study presents a data-driven lifecycle assessment (LCA) framework for evaluating greenhouse gas (GHG) emissions from passenger vehicles across European electricity systems. The analysis compares battery electric vehicles (BEVs), full hybrid electric vehicles (FHEVs), and internal combustion engine vehicles (ICEVs) using both conventional average electricity emissions factors and time-resolved marginal emissions, referred to as real charging emissions (RCE). Hourly generation and interconnector/cross-border flow data for 2023 from 29 European countries are processed to estimate consumption-based marginal emissions rates that account for grid dispatch behavior and cross-border electricity flows. The approach is applied to two vehicles where multiple powertrains are available on the same platform, the 2024 Hyundai Kona (available as a BEV, FHEV, and ICEV) and Peugeot 2008 (available as a BEV and ICEV), to isolate drivetrain-related lifecycle differences. Results show substantial divergence between average and marginal emissions estimates, with a mean absolute difference in BEV–FHEV lifecycle emissions of 31–36 g CO2 eq/km across Europe. In several countries with carbon-intensive marginal generation, including Poland and Cyprus, BEVs may exhibit higher lifecycle emissions than comparable hybrids, while low-carbon grids such as Norway, Sweden, and France provide large BEV advantages. Sensitivity analyses demonstrate the importance of transmission losses, temperature effects, electricity imports, and charging timing. These findings highlight the limitations of average grid emissions factors in vehicle LCAs and underscore the importance of geographically and temporally resolved data-driven electricity emissions when assessing electrified vehicle climate impacts.
Drew, AlfredBurton, TristanSenecal, KellyDavy, MartinLeach, Felix
This study looks into the performance traits of a pure electric car that has a continuously variable transmission (CVT) system by doing careful simulations. The research is mostly about checking how well it performs dynamically and how much better its energy efficiency is compared to regular designs. With the help of AVL Cruise software, a detailed drivetrain model was made to test things like how fast it can accelerate, its top speed, how well it climbs hills, and how much energy it uses when driven in standard ways. The simulation results show some big improvements: the CVT car can go from 0 to 100 km/h in 12.92 seconds, which is 14% quicker than expected; it can reach a top speed of 179 km/h, 15% higher than planned; and it can climb really steep hills at a 41.33% gradient. The energy efficiency analysis also found that it uses less power, consuming just 15.88 kWh per 100km under NEDC conditions and 13.72 kWh per 100km in UDC cycles, which are 21% and 24% less than before. These results prove that the CVT works well in keeping the motor running efficiently by changing ratios all the time. The study points out the technical benefits of CVT systems in making performance and energy saving balanced, but it also finds some practical problems like environmental factors and system integration issues. This work gives useful ideas for making new electric vehicle transmission systems and hints at good ways to improve them in the future.
Chen, HaishanGong, NaifaPan, YulongCai, ZhichengGao, YujieShen, XiaobingFu, XianlanChen, Keren
The way we drive has a big effect on how much energy electric cars use, so making better driving habits can help make electric cars use less energy. By utilizing a set of real EV driving data, this paper classifies and analyzes EVs from the perspective of energy consumption, and establishes an intelligent scoring system for EV driving behavior based on a decision tree model. Experimental results show that this method is able to successfully distinguish different driving behaviours and the critical driving behavior factors, such as vehicle speed, accelerator pedal change rate, etc., and braking behavior are identified. Use intelligent scoring to give driver suggestions; this way, they can improve on their driving techniques and lower their energy consumption.
Liang, YongkaiZhang, HaoLiu, YuYu, Hanzhengnan
The Active Wheel-Corner (AWC) integrates driving, braking, steering, and suspension systems into the wheel end, forming a fully drive-by-wire, four-wheel independent steering and four-wheel independent driving (4WIS&4WID) vehicle platform. While improving vehicle control performance, the full by-wire architecture also places higher demands on system reliability and fault tolerance. The steer-by-wire system has electrical, communication, and software failure risks, which may cause the vehicle to lose steering capability and trigger severe traffic accidents. This article proposes a hierarchical active fault-tolerant control strategy based on fault information reconstruction (FAST-FTC), enabling fault diagnosis and active fault-tolerant control when the steer-by-wire system fails, effectively ensuring the steering maneuverability and lateral stability of the vehicle under fault conditions. First, the strategy designs an adaptive observer combined with the Dugoff tire model to estimate nonlinear tire forces, while introducing a fault factor to achieve quantitative grading of steering system faults. Second, a hierarchical controller is designed for steering system faults. The upper-level controller, based on Adaptive Super-Twisting Sliding Mode Control (AST-SMC), determines the generalized forces required to track the desired trajectory under different fault conditions. The lower-level controller, based on the Fault-Aware Model Predictive Control (FA-MPC) strategy, dynamically adjusts weight matrices according to the fault factor and tire reconstructed stiffness, coordinating the allocation of four-wheel driving and the steering of healthy wheels to ensure lateral stability. Finally, the effectiveness of the proposed active fault-tolerant control strategy is validated through Hardware-in-the-Loop (HIL) simulation and real-vehicle tests.
Xiao, FengJiang, YueyongCheng, RuiXu, ChangheTang, XiangjiaoGao, FenglingLi, Jianhua
These days, the vehicle dynamics control of electric vehicles (EVs) with multi-actuated architectures has been widely investigated. Such EVs have a torque vectoring differential (TVD), which can generate a torque difference between the left and right wheels. As one of TVDs, a two-motor-torque difference amplification mechanism (TDA-TVD), has been proposed. The TDA-TVD can generate a greater torque difference compared to an individual-wheel-drive (IWD) system. However, it has controllability difficulties due to its two resonance modes. Previous studies first proposed a frequency response model of the TDA-TVD and anti-vibration feedforward torque controllers based on an average-differential coordinates (ADC) transformation. Subsequently, wheel speed control (WSC) and slip ratio control (SRC) based in the ADC were presented. However, only the WSC was designed with frequency domain analysis, and the SRC was designed with manual tuning. In this study, the closed loop of the SRC of the TDA-TVD is modeled in the frequency domain, and a parameter determination method based on Nyquist plot and sensitivity function analysis of the SRC, which is the outer loop of the WSC, is suggested. Next, several SRC strategies are proposed, depending on the driver’s preference. Lastly, experimental results using a real vehicle with the TDA-TVD on slippery surfaces are shown. Newly proposed and conventional SRCs are compared. The effectiveness of the proposed strategies is analyzed and presented.
Fuse, HiroyukiFujimoto, HiroshiSawase, KaoruTakahashi, NaokiTakahashi, RyotaHayashi, Takayuki
This article investigates high-frequency noise in permanent magnet synchronous motors (PMSMs) for electric vehicles, originating from pulse width modulation (PWM). A theoretical model is developed to formulate the phase voltage under space vector PWM (SVPWM), explicitly accounting for the additional harmonic components generated by the discrete-time voltage update in digital control systems. This derived voltage waveform serves as the excitation source in an electromagnetic finite-element model, from which the PWM current harmonics and their resulting high-frequency electromagnetic forces are computed. Critical components of the electromagnetic force are then extracted through two-dimensional Fourier transform. A structural model of the motor, incorporating practical assembly constraints, is established and validated by experimental modal tests on a fully assembled motor unit. To enable rapid noise prediction over the wide speed range, vibro-acoustic transfer functions are introduced. The predicted noise shows good agreement with experimental data. Leveraging this multiphysics model, the influence of switching frequency on noise characteristics is analyzed. The study identifies that avoiding excitation of the motor’s zero-order mode is critical for noise suppression. Accordingly, an optimal frequency-hopping strategy is proposed. Experimental validation confirms the strategy’s effectiveness in reducing noise over the wide speed range.
Lin, FuChen, Yihui
Uncertainty quantification (UQ) is increasingly recognized as essential when machine learning (ML) is employed in domains that are safety-relevant, cost-intensive, or legally binding, such as the product engineering of battery electric vehicle (BEV) energy systems. UQ methods aim to estimate the aleatoric, epistemic or both uncertainties associated with the predictions of a machine learning model. However, the landscape of UQ methods is diverse and rapidly evolving, with no single approach proving optimal across all tasks. Consequently, the selection of methods in practice is often driven by experience, constrained by limited comprehensive knowledge, time, and implementation capacity. This paper introduces an application-oriented process model supporting data scientists in selecting UQ methods in ML by adapting the SPALTEN [1] problem-solving methodology and the Algorithm Selection Process Model (ASPM) into an Algorithm Selection Process Model for Uncertainty Quantification (UQ-ASPM). This model can be integrated into the modeling phase of a data mining process, such as the Cross Industry Standard Process for Data Mining (CRISP-DM). Ethnographic observations and expert interviews conducted within the research environment of BEV energy system development were analyzed using inductive qualitative content analysis to identify practical barriers, motivations, and requirements. The resulting process translates task requirements and boundary conditions into UQ-specific criteria, primarily including the source of uncertainty, integration depth, and output type. It employs a funnel-like narrowing from method families to candidate algorithms and utilizes a transparent evaluation matrix with weighted criteria, consequence analysis, and learning through a continuous information pool. An illustrative predictive-maintenance example demonstrates the instantiation of the process when an existing deterministic ML model must be retained. The contribution is made at a meta-level, facilitating structured navigation of the method space rather than providing a direct comparison of individual UQ algorithms.
Holderied, NiklasHörtling, StefanBause, KatharinaDüser, Tobias
This paper presents the optimization of a Halbach magnet array applied to an axial flux machine (AFM) in a 12-pole, 18-slots yokeless and segmented armature (YASA) topology, evaluated in the torque–speed characteristics diagram. AFMs offer significant advantages in terms of compact design and high torque density compared to other permanent magnet machine topologies. However, noise, vibration, and harshness (NVH) performance is strongly influenced by cogging torque, electromagnetic torque ripple, and tooth forces. While Halbach magnet arrays are well established in high-performance radial flux machines, only limited research has investigated their influence in AFMs. A Halbach array concentrates magnetic flux on one side of the magnet arrangement, leading to increased air gap flux density and a strongly reduced need of a back iron yoke under the magnets. By using a Halbach array, the magnetic field distribution in the air gap becomes more sinusoidal, thereby reducing harmonic components. Previous studies have primarily focused on further torque enhancement or mass reduction through the elimination of back iron. Given that AFMs already exhibit high torque and power density, the objective of this paper is the reduction of NVH factors such as cogging torque, torque ripple amplitudes and tooth forces while minimizing the required magnet mass and maintaining the specified performance criteria. In the optimization process, in addition to the segmentation of the pole and transition magnets, the magnet height as well as the required thickness of the back iron yoke are optimized. For the design and optimization of the Halbach array, two-dimensional (2D) and three-dimensional (3D) finite-element (FE) models are combined with surrogate modeling techniques. In addition to the impact on torque ripple, further potential benefits of the Halbach configuration, including improvements in efficiency and reductions in overall motor weight, are analyzed and discussed.
Müller, KarstenSchulz, FabianBremer, MartinBurkhardt, YvesDe Gersem, Herbert
This paper investigates the electromagnetic and circuit-level performance of an inductive power transfer (IPT) system for dynamic wireless charging of electric vehicles (EVs). Key design parameters affecting power transfer efficiency (PTE) are examined through a simplified Series–Series (SS) compensated IPT model using a Double-D coil geometry with shielded ferrite backing, developed in MATLAB. The framework evaluates the effects of air gap, lateral misalignment, load resistance, and operating frequency on overall system efficiency. Results show that PTE is highly sensitive to spatial alignment, with significant efficiency losses at air gaps greater than 10 cm and misalignments beyond 15 cm. A combined 3D surface plot confirms the compounded nonlinear influence of both parameters. Load resistance analysis identifies an optimal range of approximately 10–15 Ω, while frequency analysis indicates peak performance near 85 kHz, consistent with standard guidelines. These findings validate trends reported in previous literature and highlight the importance of early-stage IPT system evaluation for dynamic wireless charging applications.
Abdelrahman, MarwanSodre, Jose Ricardo
The widespread adoption of electric vehicles is currently hindered by long charging durations and limited infrastructure. While fast-charging technologies address these issues, they impose significant thermal loads on high-voltage components. Within this architecture, the Battery Disconnect Unit plays a critical role as it monitors and controls the connection between the battery, powertrain, and charging system. However, the high currents required for fast-charging often drive these units' temperatures beyond safe operating limits, necessitating advanced thermal solutions that do not require extensive redesigns of the vehicle's electrical layout. To address this challenge, this study proposes a passive thermal management solution using Phase Change Material heat transfer devices to enhance the thermal robustness of the component. The methodology employs a dual approach involving initial experimental testing to pinpoint specific thermal hotspots under high-power conditions, followed by detailed numerical simulations using GT-Power software to predict system behavior. Furthermore, the paper provides a comparative analysis of various configurations, assessing their impact on temperature reduction, response time, and thermal uniformity. The results demonstrate that appropriately designed passive solutions significantly improve thermal performance, effectively enabling higher charging power capabilities while minimizing system complexity and integration effort. This innovation provides a scalable and efficient path for improving overall vehicle performance and safety during rapid energy transfer events.
Salameh, GeorgesGoumy, GuillaumeFrecinaux, AnthonyRatajczack, ChristellePalluel, MarlèneNoiseau, PascalLardeux, Sébastien
The rapid adoption of electric vehicles (EVs) with longer driving range demands high-power charging solutions that are efficient, scalable, and reliable. This work introduces a comprehensive simulation framework for megawatt-scale charging systems, focusing on the integration and control of multiple DC/DC converters. With the primary objective of maximizing overall system efficiency during megawatt-scale charging operations. A multi-agent adaptive control strategy is implemented to dynamically optimize operating points and allocate charging currents across converters in real time so that each participating converter operates at its optimal operating point where the maximum possible efficiency is delivered. This multi-agent adaptive control strategy allocates not only the individual optimal operating points of the multiple DC/DC converters but rather determines the optimal number of participating DC/DC converters at each time instance during the charging session. In addition to that, the strategy provides the option of delivering the optimal charging current during each time instance, so that maximized system efficiency is guaranteed during the charging process. Simulation results demonstrate that even a small efficiency improvement of 0.5% can yield substantial environmental benefits at a scale, where a 10 MW charging park avoids nearly 0.9 GWh of energy use and more than 350 t of CO₂ emissions over 10 years. By fully passing these efficiency gains to customers, charging becomes more affordable without compromising service provider margins, while the resulting climate benefits scale directly with utilization, installed capacity, electricity prices, and system lifetime. The proposed approach enables intelligent supervisory control for next-generation high-power charging stations, combining efficiency, cost-effectiveness, and sustainability. These findings support the development of modular, resource-efficient infrastructure for future EV ecosystems.
Salah, AliaAbu Mohareb, Omar
Battery electric vehicles (BEVs) place high demands on electric drives across a wide operating range: high efficiency in customer-related driving scenarios and maximum performance in dynamic driving modes. A promising solution to this challenge is the dynamic reconfiguration of the electric machine winding configuration between series and parallel mode, enabling optimal electromagnetic properties of the drive for different operating points. This paper presents the design and prototyping of an electronic winding reconfiguration system for high-performance traction applications. The hardware prototype has been designed and built, but has not yet been tested, which is why the results are based on simulations. Unlike mechanical winding reconfiguration concepts, which have long transition times and cannot switch under load, the proposed system enables fast and safe load transitions between the winding configurations. The study describes the topology and hardware of the switching unit, including the integration of power semiconductors, the required connection assemblies, cooling concept and the control of the power electronics. A novel control strategy is presented that ensures continuous current paths during switching, prevents overvoltage in the windings and minimises torque interruptions. To this end, the active short-circuit operation of the electric drive is taken into account. Simulations show that the system achieves efficiency gains of up to two percentage points in the partial load range while maintaining its full performance. The additional losses caused by the switching unit remain low in the partial load range, ensuring a net efficiency gain. The proposed concept offers a practical approach to extending the range of BEV drives by dynamically reconfiguring the windings of the electric machine, thereby improving partial load efficiency without compromising performance.
Oestreicher, RaphaelSchneider, Jörgvon Ohlen, DavidFuchs, PatrickKulzer, André Casal
HV Power nets of electric vehicles consist of various HV components such as batteries, inverters, auxiliaries and cables. During in-vehicle testing, multiple failures of an auxiliary inverter were observed, caused by resonance issues within the component filter. Initial investigations revealed that these resonances, absent during manufacturer testbench evaluations, were influenced by the vehicle power net and its impedance characteristics. To better understand the underlying causes and identify preventative measures, extensive simulations were performed. The results demonstrate a diminishing influence of the power net capacitance when significantly larger than the component capacitance. Also, they highlight the critical impact of cable inductance on the component resonance frequency when comparable to the component’s inductance. A simplified electrical equivalent circuit was used to derive an equation predicting the resonance frequency as a function of the component’s capacitance/inductance and the cable length to the main power net capacitances. Based on these findings, recommendations for component filter design and testing protocols were proposed to mitigate similar failures in future applications.
Schmiel, FabianAurand, TobiasKoehnlechner, BenjaminZimmer, Markus
The global automotive landscape is undergoing a significant paradigm shift driven by the rapid development cycles of emerging competitors, leaving traditional European OEMs with a critical time-to-market gap. To bridge this gap, automotive engineering must pivot from traditional hardware-based processes toward agile, digital data-driven methodologies. This paper presents a feasibility study on the implementation of data-centric approaches in component development, evaluated using the high-voltage wiring harness (HVWH) as a representative example. The HVWH serves as a practical validation case for the presented methodologies, covering both Artificial Intelligence (AI) based and deterministic methods. The study provides a detailed assessment of various AI-based and deterministic methodologies at specific stages of the product development process, targeting both product design and the product development process itself. The objective is to reduce time-to-market at the component-level by optimizing workflows, increasing process and development efficiency, and enabling knowledge reuse throughout the development process. Beyond individual method evaluation, the study examines how deterministic and AI-based approaches can be integrated into development workflows. For this purpose, process mining is first applied to identify general challenges specific to the HVWH development workflow and to derive use cases in which AI can contribute to reducing development time. From these, three use cases are selected for detailed investigation. For each use case, the necessary prerequisites, the applied methodology, the results and the limitations of AI integration are described and discussed. By integrating structured knowledge with automated workflows, the proposed frameworks allow for autonomous application of historical insights to current design parameters, streamlining the decision-making process. This semantic structure prevents the loss of critical engineering knowledge and enables continuous AI-assisted improvement across different vehicle generations. The study concludes that the proposed use cases provide a technically viable pathway to shorten development timelines, enabling European OEMs to match the speed of competitors while maintaining high standards of quality, functionality and safety.
Bode, Jana PascalKröll, SarahVohwinkel, NikolausPaetzold-Byhain, Kristin
This paper presents Stochastic Gradient Pulse Adaptation (SGPA), a real-time adaptive pulse-charging system for rechargeable electrochemical batteries that dynamically adjusts charging aggressiveness based on the battery's internal response, as opposed to predetermined CC–CV or fixed pulse profiles. SGPA is different from traditional charging methods that use static current de-rating and conservative voltage limits. Instead, SGPA uses gradient-based feedback from terminal voltage behaviour, temperature changes, internal resistance changes, and state of charge to continuously adapt pulse amplitude and duty cycle. This algorithm boosts the charging intensity when the electrochemical circumstances are good. It lowers the pulses slowly when signs of thermal or impedance-related stress show up. Simulation-based proof-of-concept experiments on a heavy-duty multi-battery system show that charging time is less than with multi-CCCV charging, while still keeping the current distribution across packs balanced. The suggested SGPA method adds an adaptive charging algorithm that is easy to understand and ready to use. It makes fast charging more efficient without lowering voltage and thermal safety limits.
Prakashkumar, BalagopalMannar, Vignesh
This SAE Surface Vehicle Technical Information Report, SAE J2836/4, establishes diagnostic use cases between plug-in electric vehicles (PEV) and the electric vehicle supply equipment (EVSE). As PEVs are deployed and include both plug-in hybrid electric (PHEV) and battery electric (BEV) vehicle variations, failures of the charging session between the EVSE and PEV may include diagnostics particular to the vehicle variations. This document describes the general information required for diagnostics and SAE J2847/4 will include the detail messages to provide accurate information to the customer and/or service personnel to identify the source of the issue and assist in resolution. Existing vehicle diagnostics can also be added and included during this charging session regarding issues that have occurred or are imminent to the EVSE or PEV, to assist in resolution of these items.
Hybrid - EV Committee
The electrification of heavy-duty vehicles is a critical pathway toward improved energy efficiency in the freight sector. The current battery electric truck technology poses several challenges to commercial vehicle operations, such as limited driving range, sensitivity to climate conditions, and long recharging times. Estimating the energy consumption of heavy-duty electric trucks is crucial to assessing the feasibility of fleet electrification and its impact on the electric grid. This article focuses on developing a model-based simulation approach to predict and analyze the energy consumption of electric trucks by considering the impact of weather and geographical conditions on vehicle road load and auxiliary components power consumption, as well as the impact these factors have on driving range. Specifically, drayage trucks employed in logistics around maritime ports are used as a case study, with consideration of seasonal climate variations and geographical characteristics at different locations. The article includes results for three major container ports within the United States, providing region-specific insights into the energy requirements and driving range of the electric drayage trucks in these regions, which will inform decision-makers in integrating electric trucks into the existing drayage operations and plan investments for electric grid development.
Shiledar, AnkurVillani, ManfrediLucero, Joseph N. E.Sun, RuixiaoSujan, Vivek A.Onori, SimonaRizzoni, Giorgio
This SAE Information Report SAE J2836/6 establishes use cases for communication between plug-in electric vehicles and the EVSE for wireless energy transfer as specified in SAE J2954. It addresses the requirements for communications between the on-board charging system and the wireless EV supply equipment (WEVSE) in support of detection of the WEVSE, the charging process, and monitoring of the charging process. Since the communication to the charging infrastructure and the power grid for smart charging will also be communicated by the WEVSE to the EV over the wireless interface, these requirements are also covered. However, the processes and procedures are expected to be identical to those specified for V2G communications specified in SAE J2836/1. Where relevant, the specification notes interactions that may be required between the vehicle and vehicle operator, but does not formally specify them. Similarly, communications between the on-board charging sub-system and the on-board vehicle electronics is not formally specified in this document. This document will be published as a set of steps. The intent of step 1 was to record as much information on “what we think works” and publish. The intent of step 2 is to provide refinement and missing pieces to step 1, with a an eye to early testing. This version is step 2, with the aim of providing a communication protocol for home chargers.
Hybrid - EV Committee
This document provides recommendations involving BEV battery data retention and battery design that enhance the potential for BEV battery reuse and serviceability and that can improve recyclability. These recommendations have been developed by a group of professionals skilled in the secondary-use of batteries and in the research, development, and manufacture of BEV batteries and battery systems.
Secondary Battery Use Committee
Interior acoustics represent an essential component of driving comfort in electric vehicles. Numerical simulation is an effective approach for assessing design concepts and enhancing acoustic performance. However, a fully coupled vibro-acoustic model for an entire vehicle remains computationally infeasible. Our approach couples mechanical and acoustic modal models on non-conforming interfaces in the low-frequency range, allowing independent mode combinations. Modal coupling reduces the computational effort significantly from full-order systems with millions of degrees of freedom to a selection of modes of the acoustic and mechanical systems. Modal models of the vehicle structure are derived from measurements with a laser-vibrometer and accelerometers while the interior acoustics are simulated numerically. Since laser-vibrometer measurements are restricted to the vehicle’s exterior surfaces and vibro-acoustic coupling occurs between the inner structural surface and the interior fluid, the structural behavior of the vehicle’s inner surface needs to be determined. We performed modal testing on both the exterior and interior surface of a front door within an entire vehicle due to volume source excitation on the inside of the vehicle. The modal structural behavior of the exterior and interior surfaces for the frequency range of interest already showed an indication of a door dynamic. For a mathematically consistent application of modal coupling method, the eigenvectors of the acoustic and mechanical subsystems must be correctly scaled, i.e. they must be mass-normalized. While the acoustic modes obtained from numerical simulation inherently fulfill this requirement, the mechanical modes extracted from experimental data generally do not. To address this challenge, we investigated a flat plate in numerical simulation and derived a method to determine scaling factors for obtained mode shapes. Proper scaling of the mechanical modes was achieved by applying the scaling method on our measured door modes. The coupled simulation reveals an inherent dynamic behavior of the door.
Gutbrod, ManuelGabriel, ChristophMüller, Gregor JohannesToth, Florian
Simplicity and electrification of the propulsion system are one of the most important trends in vehicle development and integration process. The complexity of NVH (Noise, Vibration and Harshness) design and refinement is the core challenge to this process. Customers’ expectations of an unnoticeable engine during driving make this challenge more critical [1]. Apart from the overall sound pressure level, the sound quality is even more important due to the lack of noise masking effects [2]. Therefore, the development team has reached an internal consensus that NVH attributes are the top priority in engine development. This paper describes the NVH development process of a dedicated hybrid engine for the range extender electric vehicle (REEV) application, beginning with an introduction to REEV system as well as the operating condition data of long-distance road tests. Based on the road test data, the engine technical specification is defined accordingly and broken down into design targets for all individual components. Subsequently the design target is finally achieved through the definition of engine architecture, hardware selection, and individual component simulation and optimization. With regard to the NVH refinement, the NVH issues such as global crankshaft vibration, start impacts, high-pressure fuel system ticking, and acoustic encapsulations studies are discussed. Finally, the appropriate optimization proposals are summarized and the bench test results are presented.
Wang, HaoZhang, Guiqiang
Although propulsion noise often constitutes a minority of the overall noise in electric vehicles, it remains an important quality indicator due to its high-frequency tonal character, which is undesirable even at low levels. There are many factors that influence the interior car levels of propulsion noise, i.e. gear whine and electric motor whine. The primary ones to consider are the electric drive units (EDU) internal forces, but also secondary properties such as EDU housing design and encapsulation, vehicle sound pack and mount isolation play important roles. This work focuses on EDU housing design and more particularly on the housing ribs that enables attachment point stiffness and housing strength, but which can also cause problems in terms of noise radiation. Numerical parameter studies on geometrical properties such as length dimensions, thickness and curvature were performed on single ribs of different types. For each design iteration, the key performance indicators radiated sound power, squared velocity and radiation efficiency were studied. The outcome of this work provides insights into which characteristics of ribs that are central for radiated noise. For instance, it was proven that a rather small curvature of the outer edge of a rib can decrease the radiated noise but also that certain rib dimensions can result in extensive noise due to the interaction of the first bending mode with the peak in radiation efficiency.
Lennström, DavidMalm, Oskarwurzinger, JakobCederlund, Johan
In vehicles with electrified powertrains, high-frequency tonal noise components have become increasingly prominent and can be perceived as particularly annoying by the driver. While recent advancements in international standardization — such as ECMA-74 [1] and ECMA-418 [2] — have led to powerful new algorithms for tonal noise visualization and analysis, including Tonality-Heatmaps, the measurement side still lacks sensor setups that adequately reflect the spatial sensitivity of noise, especially for tonal components. This challenge is amplified in enclosed vehicle cabins, where room modes create local minima and maxima that become increasingly dense at higher frequencies. As a result, even small head movements can lead to noticeable differences in perceived tonal noise. Current measurement approaches do not sufficiently account for this spatial variability. This contribution addresses the absence of tailored solutions for the driver’s position by introducing an improved microphone arrangement that significantly reduces the uncertainty of measured noise levels. The proposed setup considers spatial variability without compromising comfort or crash safety requirements. By enhancing the precision of tonal noise quantification, this approach provides noise-vibration-harshness (NVH) engineers with a valuable complement to modern software-based tonal analysis methods. The paper discusses the technical implementation constraints and demonstrates the comparability of the new measurement technique with conventional setups.
Schecker, DanielRittenschober, Thomas
The increasing electrification of vehicles means that heating, ventilation and air conditioning systems have a broader range of tasks and a different priority assessment. In electric cars, air conditioning systems are not only responsible for cooling the passenger compartment, but also for controlling the battery temperature, particularly during rapid charging, which represents a high-load operating point. Furthermore, achieving high thermodynamic efficiency is desirable, as this directly impacts the range of electric cars. The elimination of the combustion engine as a major source of noise prioritizes the noise, vibration and harshness behavior of the refrigerant compressor for product selection. To investigate the vibration and acoustic behavior, as well as the fluid dynamic forces resulting from the cyclic compression principle of an electric refrigerant compressor, a test rig was developed that allows compressors to be operated and measured in isolation in an anechoic chamber under various defined operating conditions. This test rig has been expanded in two ways within the scope of this work. Firstly, the compressor can be either rigidly attached to a dead mass using a VDA mount or measured while suspended freely. Secondly, a new R744-compatible refrigeration circuit has been added to the test rig, enabling compressors operating with the environmentally friendly refrigerant CO₂, which has so far only been used by a few manufacturers in selected models, to be tested. Measurement results obtained using this test rig provide valuable insight into the vibration behavior and sound spectra of the refrigerant compressor's fluid, structural, and airborne noise when operating at different points.
Beer, GabrielSaur, LukasSchwarz, ManuelZemsch, StefanBecker, Stefan
In electrified vehicles, auxiliary components can represent a dominant source of noise, one of which is the refrigerant scroll compressor. Compared with vehicles equipped with internal combustion engines, electrified vehicles require larger refrigerant compressors, as thermal management is needed not only for the passenger compartment but also for the battery and electric drive components. Excitation mechanisms within the compressor, arising from the cyclic compression process and the eccentric motion of the scroll, induce housing vibrations and result in airborne sound radiation. To investigate the vibroacoustic noise generation mechanisms of a scroll compressor, operational vibrations were analysed using accelerometers and three-dimensional laser scanning vibrometry. In addition, the radiated sound was characterised using microphones and near-field sound intensity measurements. The results demonstrate a strong correlation between surface vibrations and airborne sound radiation, with the vibroacoustic behaviour being dominated by speed-dependent tonal components. Pronounced vibration and sound radiation levels occur when excitation orders coincide with rigid-body modes of the mounting system or structural eigenmodes of the compressor housing. Based on these findings, a constrained-layer damping treatment was applied to selected, highly sound-radiating regions of the compressor housing. Although the overall reduction in sound power was limited due to the high stiffness and predominantly rigid-body behaviour of the housing, local vibration and sound radiation reductions were achieved for structurally flexible components, resulting in a perceptible improvement in subjective sound quality. These results highlight the importance of spatially resolved vibroacoustic analysis for understanding noise generation mechanisms and for guiding targeted optimisation measures for refrigerant compressors.
Saur, LukasBeer, GabrielFritzsche, MarcoBecker, Stefan
Tire exterior noise has become increasingly critical in vehicle acoustics due to two key developments: updated pass-by noise regulations, which amplify the relative contribution of tire noise, and the rise of Battery Electric Vehicles (BEVs), which lack traditional powertrain noise. Design trends in BEVs—such as increased vehicle mass from battery packs and the widespread use of large-diameter, wide, low-profile tires—further intensify tire noise due to stiffer constructions and altered contact dynamics. A common method for predicting tire noise is the source-transfer-receiver model, where the tire is represented by a set of monopoles with volume velocity Q derived from near-field measurements. Acoustic propagation is modeled via p/Q transfer functions. Despite its simplifications, this approach is practical for vehicle development, enabling clear separation between source and transfer mechanisms and facilitating targeted noise control strategies. In previous work, we proposed a rigorous framework to optimize both the spatial distribution and strength of the monopole sources. Positions were identified using an L1-norm regularization via the Lasso algorithm, promoting sparsity and physical interpretability. Strengths were estimated using an L2-norm Tikhonov regularization, which stabilizes the solution against measurement noise. While the Tikhonov regularization parameter was previously tuned manually through trial and error, we now enhance predictive accuracy by selecting it via a cross-validation technique, ensuring a more robust and data-driven optimization. Besides this, compared to the previous work the approach here is validated for the prediction of both indoor and outdoor pass-by noise, as well as for multiple tire types providing different noise levels. Results demonstrate the method’s robustness, accuracy, and applicability for acoustic development in modern vehicle platforms.
Morin, BenjaminDi Marco, FedericoHorak, JanLafont, ThibaultKim, MinkyuKang, Min KyooYoo, Ji Woo
Vehicle electrification and accelerated development cycles create a need for virtual Noise, Vibration and Harshness (NVH) development tools which are fast, precise and, seamlessly interchangeable between development sites, suppliers and OEMs. Component-based Transfer Path Analysis (C-TPA), standardized in ISO 20270:2019, enables independent component characterization and integration with virtual models to predict sound and vibration in new assemblies, referred to as Virtual Prototype Assemblies (VPA). However, conventional measurements are labor-intensive, typically restricted to a small number of samples, and overlook production variability. This paper introduces a fully automated, ISO 20270-compliant C-TPA system for non-rigid test benches, featuring a pre-instrumented test fixture with multiple vibration shakers and sensors automatically linked to a data acquisition system for immediate processing. Components can be characterized within minutes, with blocked forces directly integrated into a VPA workflow, replacing time-intensive in-vehicle testing with a repeatable, operator-independent bench procedure. A case study on an automotive steering system demonstrates the method’s accuracy, repeatability, and efficiency, along with its ability to predict realistic interior sound pressure levels and capture production variability, enabling robust virtual NVH evaluation early in the development cycle.
Sturm, MichaelWienen, KevinBrandstetter, MarkusSorber, EricCorbeels, PatrickVerrecas, BartGonçalves, Vinícius
Vehicle sound packages are usually designed to provide a given level of vehicle Noise, Vibration, and Harshness (NVH) comfort, within weight and cost constraints. Optimal comfort results can be obtained by considering the interaction of all the parts as a full physical system. So far, extensive research has already been performed and published on optimizing vehicle sound packages to achieve effective noise reduction at lowest cost and weight. Nowadays, due to the urgency of the transition to carbon neutrality, sound packages must also address the reduction of the full vehicle life cycle carbon emissions. Sound package components should use materials that have a low emission impact during production and that are suitable for recycling at the end of the vehicle’s life. This entails reconsidering the material solutions chosen for the sound package as a whole, rather than for each individual component. This article describes possible differentiations in the design of a sound package involving NVH, sustainability, and weight/cost requirements. The study examines how interior and exterior trim components were combined to achieve both optimal NVH and polymer rationalization, through the introduction of mono-material parts and focusing in particular on the use of a new polyester fiber-based floor decoupler, which achieves comparable NVH performance to polyurethane foam without affecting static compression. The article summarizes the vehicle-level performance related to NVH, sustainability, and weight for three sound packages prioritizing either NVH, sustainability or material cost, including a breakdown to analyze the contributions of various components to the overall outcome. A simple metric is introduced to evaluate sustainability, including material, production, use-phase and end-of-life related Greenhouse Gas (GHG) emissions [7–10]. The NVH evaluation involves measuring airborne transfer functions (ATF), complemented by indoor road noise tests. NVH improvements were achieved without an increase in weight, and weight reduction was also possible without negatively impacting NVH performance, both results enhancing the carbon footprint.
Courtois, TheophaneCardillo, MarcoCriscione, MattiaGerges, YoussefMassocco, Andrea
Vehicle electrification and increasing demands for driving comfort present significant challenges for designing effective noise control treatments (NCTs) in modern vehicles. Lightweight, low-emission designs often compromise acoustic efficiency. A popular and efficient way of compensating for this is through the use of multi-layer ‘trim’ material configurations to noise radiating surfaces to mitigate noise across a wider frequency range. Traditional 3D finite element models, while accurate and even needed to capture the full dynamic behaviour, become computationally prohibitive for complex automotive structures like firewalls, which feature intricate shapes, high curvature, and material compression. This computational burden limits design exploration and timely noise performance predictions. To overcome these limitations, this paper presents an innovative adaptive higher-order finite element method to evaluate the sound transmission loss (STL) of automotive, including the effect of poro-elastic and viscoelastic soundproofing materials. To show its capabilities, a digital twin was developed for a STL test setup for a production vehicle firewall with and without NCT. We present simulation results for different firewall configurations, comparing them against experimental data for the panel STL levels and relative improvements due to a NCT modification. The findings demonstrate the method's accuracy, efficiency, and applicability to real-world automotive engineering problems and also shed light on the trade-offs between model idealization and fidelity of the digital twin.
Van Genechten, BertVansant, KoenPurohit, BimalEffinger, Veronika
Electric vehicle subsystems, including powertrains, electric motors, and gearboxes, pose new challenges in achieving stringent acoustic performance targets for both interior and exterior noise. These challenges are intensified by increasingly demanding customer expectations regarding interior acoustic comfort, which encompasses the reduction of intrusive noise sources and the enhancement of overall sound quality across a broad frequency spectrum. A primary concern associated with electric vehicles subsystems is the generation of high-frequency tonal noise, commonly referred to as whine noise, which can significantly impact acoustic performance and passenger comfort. High-frequency whine noise propagates through multiple transmission paths and can be effectively attenuated at the source through encapsulation strategies, which also contribute to broadband noise reduction across a wide frequency spectrum. To predict the acoustic performance of encapsulation, a coupled simulation approach combining the Boundary Element Method (BEM), the Finite Element Method (FEM) and the Poroelastic Finite Element Method (PEM) has been developed. This methodology has been already presented and validated through experimental measurements, demonstrating its acoustic effectiveness in the encapsulation of a generic electric motor housing. While BEM is well-suited for modeling exterior acoustic propagation, standard implementations encounter limitations at high frequencies due to mesh density requirements and computational cost. This work presents hybrid parallelization strategies that integrate frequency-domain decomposition with multi-threading to accelerate BEM H-matrix computations. Frequency decomposition enables parallel processing by distributing independent frequency tasks across multiple processes, while multi-threading enhances performance for fine-grained operations such as matrix assembly and H-matrix compression within each frequency. The processes and improvements enabled by these strategies are discussed and presented within an adapted high-performance computing (HPC) environment.
Amichi, KamelCalloni, Massimiliano
Space vector pulse width modulation (SVPWM) induces common-mode voltage (CMV) in three-phase voltage-source inverters, producing steep voltage edges that can lead to high leakage currents. In electric drive applications, these currents accelerate motor bearing degradation and may cause winding insulation failure. Active-zero-state PWM (AZSPWM) and near-state PWM (NSPWM) have been proposed as alternative modulation strategies to mitigate CMV and reduce drive degradation. This paper investigates the noise, vibration, and harshness performance of AZSPWM and NSPWM in comparison with conventional SVPWM. The proposed CMV reduction schemes are evaluated in terms of both CMV mitigation and their impact on high-frequency sideband vibration harmonics. Experimental results demonstrate that the CMV reduction strategies are highly effective in lowering CMV levels relative to SVPWM; however, this benefit is accompanied by an increase in vibration levels, which may adversely affect the mechanical integrity of the drive system despite the reduction in bearing leakage currents.
Khamis, Mahmoud AlyTatar, Andrei AlexandruRepecho, VictorDoria-Cerezo, Arnau
The deployment of high-power DC charging infrastructure for electric vehicles introduces new challenges in managing noise, particularly in public environments where acoustic comfort and regulatory compliance are essential. Noise emissions from both charging stations and vehicles during charging are a concern for operators of charging parks regarding customer experience and noise immission regulations. AVL employed a structured three-step approach to develop a non-expert tool for assessing the noise radiation of charging stations and vehicles during the charging phase. In a first step, AVL characterized the noise emissions with sound power measurements. Secondly, the measurement results were transferred to the virtual domain. To achieve this, the vehicles and charging station were characterized in the simulation with multiple monopole sources supported by transfer function measurements. This simulation model was validated against the sound power measurement results. After successful correlation of the simulation model, AVL implemented a user-friendly noise mapping tool for predictive planning of charging parks moving from a 3D FEM simulation approach to a simplified noise radiation model according to ISO 9613. Measurements were conducted on a representative high-power DC charging station and two electric vehicles. The vehicle cooling fan was identified as the dominant noise source on the vehicle side, while internal cooling fans of the charging station were the primary contributors to the noise radiated by the charger. Noise emissions were found to increase with higher charging currents, indicating a strong dependency on thermal load. The project established a reusable workflow for acoustic source identification enabling the creation of a scalable database. The noise mapping tool allows easy prediction of noise radiation from multiple charging stations and vehicles during the planning phase of charging parks and supports the design of countermeasures to meet regulatory requirements.
Gojo, JosefPolanz, MarkusGraf, BernhardLangjahr, PacoMehrgou, Mehdi
Electric vehicles (EVs) and internal-combustion-engine vehicles (ICEVs) differ fundamentally in their in-cabin acoustics, notably the attenuation or absence of engine-order content. Prior work reports associations between reduced engine sound, speed underestimation, and poorer speed maintenance; however, research on how EVs’ new sound affects speed perception and control is scarce, and most newer studies focus on comfort and subjective pleasantness rather than speed perception. Addressing this gap, the present study uses a two-interval, two-alternative forced-choice (2AFC) paradigm to directly measure just-noticeable differences (JNDs) in speed under ICEV, EV, and silent conditions. Thirty participants performed a 2AFC task in which, on each trial, they viewed two first-person highway clips (reference vs. comparison) and indicated which appeared faster. Results from ANOVA and post-hoc tests indicate that at the 40 km/h reference speed participants showed no clear differences across sound conditions, whereas at 100 km/h there were marked differences in JND: mean values were 1.93 km/h (ICEV), 3.48 km/h (EV), and 5.15 km/h (silence). A psychoacoustic parameter analysis suggests that this effect is not explained by speed-dependent changes in loudness or sharpness; we interpret that RPM-related, clearly audible frequency shifts in ICEV provide the primary contributory cue. For EV NVH or artificial sound design, enhancing speed-contingent, trackable spectral cues while respecting comfort may help maintain drivers’ ability to discriminate speed differences.
Li, ZhenxianParizet, EtienneColangeli, Claudio
This study presents a high-fidelity NVH (Noise, Vibration, Harshness) analysis model development process for EV traction motors. The proposed process consists of two main components: Path advancement through structural stiffness tuning, and Source advancement, focused on the motor’s excitation mechanisms. Model accuracy was validated through comparison of simulation results with dyno experiment data, with particular focus on the 24th-order electromagnetic vibration observed in an 8-pole, 48-slot motor. Path advancement was achieved through modal correlation between experimental results and finite element (FE) analysis. Nine modal experiment and simulation stages were conducted, ranging from individual components to the complete motor assembly. Mode shapes were compared using the Modal Assurance Criterion (MAC), and natural frequencies were matched within a 5% error margin by adjusting FE material properties. For the 24th-order electromagnetic vibration, simulation results agreed with experiment data within a 7% error margin for natural frequency. However, notable discrepancies remained in vibration amplitude. To resolve these discrepancies, Source advancement was performed. The initial excitation source was derived from idealized electromagnetic analysis, considering radial and tangential force as well as torque ripple. However, rotor eccentricity caused by mechanical assembly tolerances is commonly observed in actual motors. Therefore, the advanced source accounted for rotor–stator eccentricity in the electromagnetic analysis. As a result, the NVH simulation incorporating the advanced source matched the vibration amplitude within a 1% error margin compared to experimental results. The proposed NVH model development process enables more accurate vibration prediction in the early design phase of electric drive motors and is expected to significantly improve NVH performance in future electric drive systems.
Kim, DongheeKim, Dong-JunLee, SangHanKim, Seon HyeongHwang, Seung GyuValente, GiorgioParisouz, ShahriarHalse, Christopher
The virtual development of Electric Drive Modules (EDMs) for Battery Electric Vehicles (BEVs) requires proven and predictive methodologies. One part of the development investigates the vibro-acoustic assessment for the low- and high-frequency ranges within the targeted operating range. The efficient use of such a methodology requires an understanding of the accuracy and validity of the achievable results, as well as the derivation of suitable improvement measures for goals that have not been achieved. The use of reference data from experimental investigations and a detailed root cause analysis (RCA), to directly link a specific response and behavior to the excitations, modal content, and transfer functions, is an essential and non-trivial part of the methodology development. This paper describes the development of such a methodology using the example of a new EDM virtual model for Noise, Vibration and Harshness (NVH) analysis, including the simulation approach, validation, and evaluation procedure. It discusses how RCA can be applied to different observed phenomena in EDM NVH behavior and detected deviations between the initial model and the measurements, the main influencing parameters, and the identified improvement potential for simulation models.
Klarin, BorislavPevec, DenisResch, ThomasEsposito, SaraD'Alessandro, VincenzoSpanu, Giorgio
Items per page:
1 – 50 of 5111