Browse Topic: Electronic control systems

Items (4,113)
Recent advances in precision motion technology have heightened the requirement for precise stiffness analysis in flexible mechanisms. This paper begins with a theoretical analysis, constructing a mathematical expression for the stiffness of flexible mechanisms, providing a systematic framework for analysis. Subsequently, the study employed finite element analysis on both single and double parallelogram flexible mechanisms to validate the proposed theoretical stiffness formulas. This process not only confirmed the effectiveness of the proposed expressions but also highlighted the influence of different structures on stiffness characteristics. The finite element analysis results validate the proposed theoretical model as an effective and reliable tool for predicting the stiffness of flexible mechanisms. By establishing a reliable predictive model, this research paves the way for the informed design and systematic optimization of next-generation flexible mechanisms in precision motion engineering.
Cai, Dongchen
The propeller-driven Bernoulli adsorption device (PBD) has both propulsion and adsorption functions, being suitable for dual-mode underwater robots. Currently, there have been studies on the adsorption performance of PBD on the flat surface. However, the surface morphology of underwater engineering structures is different, and PBD’s adsorption performance on irregular walls still remains unknown. In this letter, based on the potential application scenarios of underwater dual-mode robots, we established four types of irregular wall models to investigate PBD’s adsorption performance on irregular walls. Through CFD simulations and experiments, the adsorption state was analyzed, and the adsorption performance was quantitatively studied.
Liu, SiyueHua, ZhongYang, Canjun
Under China’s intelligent manufacturing strategy, manufacturing enterprises are expected to achieve digital and networked operations by 2025, with full digital transformation by 2030. Intelligent factories, the core of this transformation, rely on interconnected, integrated, and data-fused systems. This paper focuses on the micro-assembly intelligent workshop at the Nanjing Research Institute of Electronics Technology, which produces micro-circuit modules for large-scale complex electronic systems. The workshop combines discrete and process manufacturing modes, presenting unique challenges for digital management. A digital management platform based on a five-layer architecture (device, network, data, application, and decision layers) is proposed to address multi-dimensional business needs, including production scheduling, logistics, execution, and decision optimization. A hierarchical workflow structure of the workshop, consisting of a main workflow and several sub-processes, is in-depth studied and designed. The platform is constructed based on requirements analysis and workflow design of the workshop and integrates systems such as MES, APS, WMS, and SCADA, supported by AI-driven big data analytics. This study offers a practical framework for advancing digital transformation in the electronics industry.
Zhang, JianWang, JiafengGuo, Yongzhao
PID
Lin, JingDeng, ZhixiangXu, JunWu, HuankunGuan, BinLiu, Lei
This paper proposes a nonlinear and robust State-Dependent Riccati Equation (SDRE) combined with H∞ control architecture for brake- by-wire systems, specifically designed to handle severe tire-road friction variations and μ-split scenarios. The primary objective is to maximize deceleration capabilities while rigorously maintaining yaw stability, trajectory tracking, and passenger comfort through jerk limitation. Situated within the domain of active safety, this research addresses robustness against real-world uncertainties by utilizing a high-fidelity 14-degree-of-freedom vehicle model that accounts for longitudinal, lateral, and yaw dynamics, suspension-induced pitch and roll effects, and nonlinear tire behavior with explicit load transfer. To ensure near-optimal slip tracking under variable surface conditions, the system employs online friction estimation via Extended and Unscented Kalman Filters (EKF/UKF) fusing wheel and IMU data to adaptively adjust slip targets. The control strategy is bifurcated: the SDRE component manages dominant nonlinearities through state-dependent gains to prevent wheel lock-up, while the H∞ component provides robust disturbance rejection against parametric uncertainties such as mass variations and sensor noise. Control efforts are distributed via a Quadratic Programming (QP) torque allocator featuring anti-windup mechanisms and explicit saturation handling to compensate for lateral drift during μ-split braking. Validation is conducted through a Model- in-the-Loop (MIL) to Software-in-the-Loop (SIL) pipeline using scenarios including wet surfaces and panic braking. Simulation results demonstrate enhanced yaw stability and controlled deceleration profiles compared to conventional baselines, ensuring computational feasibility for automotive Electronic Control Units (ECUs).
Cubillos, Ximena Celia Méndez
This study presents a full-envelope attitude-stabilisation and trajectory-tracking strategy for morphing flying-wing UAVs operating in highly nonlinear and strongly coupled conditions. The approach integrates fuzzy C-means (FCM) envelope partitioning with L1 adaptive control. Small-disturbance linear models are first generated at multiple altitude–Mach trim points; the FCM algorithm then performs unsupervised clustering in the state space, yielding representative subintervals that capture local flight-dynamic characteristics. The optimal cluster number and fuzziness exponent are selected using the partition coefficient, partition index, partition entropy, and Xie–Beni indices. For each sub-interval, an LQR baseline controller is designed and augmented by an L1 adaptive compensator, where a low-pass filter decouples adaptation from robustness to guarantee specified transient-performance bounds under matched/unmatched uncertainties, actuator saturation, and external disturbances. A feed-forward pre-filter realises online decoupling of the multi-input multi-output channels, thereby enhancing adaptability to variable sweep angles and large aerodynamic variations. Simulations covering low-speed/small-sweep and high-speed/large-sweep scenarios demonstrate that the proposed method sustains robust stability across the clustered envelope, outperforming conventional control schemes and confirming its engineering applicability.
Tang, LonghaoSun, XiaoxuLiu, Changlin
Series hybrid electric vehicles (HEVs) employ an electric motor for propulsion, while the internal combustion engine operates solely as a generator under energy-efficient speed and load conditions. Owing to this architecture, series HEVs can achieve high fuel efficiency with a relatively simple control structure. However, conventional energy management systems (EMSs) often prioritize battery state-of-charge (SOC) stabilization, which can lead to frequent engine start–stop operations and unnecessary fuel consumption, particularly in short-trip driving. This study aims to enhance energy management performance in series HEVs by optimizing engine power generation timing based on predicted short-trip duration. A computationally efficient, rule-based prediction model is developed using real-world driving data, in which short-trip duration is estimated from vehicle speed and acceleration. Due to its low computational load, the proposed model is suitable for implementation in an onboard electronic control unit (ECU). The proposed control strategy initiates engine power generation when the battery SOC is low and the predicted trip duration is long, and suppresses generation when the SOC is sufficiently high or the predicted trip is short. A detailed vehicle model incorporating an engine, generator, electric motor, inverter, and battery is developed in Modelica to evaluate the proposed strategy. Simulation results demonstrate that the proposed EMS significantly reduces the frequency of engine start–stop events, leading to fuel economy improvements of 3.6% under the WLTC (excluding the extra-high phase) and 13.4% in a real-world urban–rural driving cycle, compared with a commercialized baseline vehicle. These results confirm the effectiveness and practical applicability of the proposed EMS for passenger vehicle applications.
Mizushima, NorifumiSato, AkiraKuboyama, TatsuyaMoriyoshi, Yasuo
Next-generation powertrain architectures proposed within EU Horizon projects adopt operating voltages above 800 V, providing improvements in efficiency as well as reductions in copper usage and system weight. However, post-800 V vehicles must remain backward compatible with existing 400 V and 800 V charging infrastructure, which requires the installation of an additional onboard DC boost charging unit on the vehicle. This paper proposes an integrated DC boost charging solution that reutilizes the open-end winding electric machine and the traction inverter of the electric powertrain, enabling backward compatibility while further reducing system cost and weight. In charging mode, the electric machine is repurposed as a passive inductive component, imposing a strict requirement of stationary operation with zero torque generation, which fundamentally differs from the driving mode characterized by rotor rotation and electromagnetic torque production. Consequently, conventional electric machine modeling approaches based on the rotor-oriented reference frame are not applicable to charging operation due to the unsymmetrical and unbalanced three-phase currents in the machine windings. To evaluate the machine behavior and develop charging control strategy, this paper introduces a magnetic-domain model based on physical model using phase self- and mutual-inductance parameters, from which the electromagnetic torque is directly derived based on the interaction between magnetic flux and phase currents. The simulations compare the charging current ripple and electromagnetic torque generation of a stationary open-end winding machine under two charging configurations: open-winding charging and neutral-point charging. The results show that the open-winding charging configuration exhibits lower current ripple than the neutral-point charging configuration due to higher inductance utilization. However, a non-zero charging torque is generated in the open-winding charging configuration and is strongly dependent on rotor position. The specific rotor positions corresponding to zero torque are identified and used to optimize the charging process.
Wang, HaoranKallur-Krishnamoorthy, RajeshNeuhaus, ChristophAndert, Jakob
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
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
Electronic Control Units (ECUs) have played a pivotal role in transforming motorcars of yore into the modern vehicles we see on our roads today. They actively regulate the actuation of individual components and thus determine the characteristics of the whole system. In this, the behavior of the control functions heavily depends on their calibration parameters which engineers traditionally design by hand. This is taking place in an environment of rising customer expectations and steadily shorter product development cycles. At the same time, legislative requirements are increasing while emission standards are getting stricter. Considering the number of vehicle variants on top of all that, the conventional method is losing its practical and financial viability. Prior work has already demonstrated that optimal control functions can be automatically developed with reinforcement learning (RL); since the resulting functions are represented by artificial neural networks, they lack explainability, a circumstance which renders them challenging to employ in production vehicles. In this article, we present an explainable approach to automating the calibration process using residual RL which follows established automotive development principles. Its applicability is demonstrated by means of a map-based air path controller in a series control unit using a hardware-in-the-loop (HiL) platform. Starting with a sub-optimal map, the proposed methodology quickly converges to a calibration which closely resembles the reference in the series ECU. The results prove that the approach is suitable for the industry where it leads to better calibrations in significantly less time and requires virtually no human intervention.
Kampmeier, AndreasBadalian, KevinKoch, LucasLee, Sung-YongAndert, Jakob
Vehicle software updates are released more frequently and in increasingly shorter cycles, which places growing pressure on vehicle quality and final assembly line stability. In production environments, software related issues do not remain limited to the digital domain, since errors introduced by software updates can interrupt flashing and commissioning processes, slow down assembly, and increase rework, thereby directly affecting production throughput. Electronic control units are particularly sensitive to software updates because they are flashed and commissioned during vehicle production under strict timing constraints, and changes to flashing sequences, memory structures, configuration parameters, or function definitions can negatively influence commissioning behavior. This paper presents a novel approach where an established quality measure – First Time Quality (FTQ) – is used to quantify the impact of software updates in the final assembly. By comparing FTQ values from production weeks with software updates to reference weeks without software changes, the analysis identifies total FTQ deviations of 7 to 11 percentage points relative to a reference level of approximately 98.6 percent for major software releases. A two-stage root-cause classification combining automated error categorization with expert validation attributes approximately 3 to 4 percentage points of this deviation to software-update-related commissioning errors. Wilson score confidence intervals and Newcombe intervals confirm that these deviations are statistically robust at production-scale sample sizes. FTQ recovery to reference levels typically occurs within one to three weeks after a major release. Using real production data from a vehicle plant, the analysis demonstrates that even comparatively small reductions in FTQ indicate a relevant degradation of production quality and can propagate into downstream quality behavior. These findings show that FTQ is a suitable and production relevant indicator for determining the impact magnitude of software updates in automotive manufacturing and for supporting data-driven decisions in the software release process.
El Asad, AimanKöhler, KatjaHahn, MichaelReuss, Hans-Christian
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 transition from internal combustion to electric vehicles requires assessing new challenges posed by novel components, materials, and manufacturing processes. These include assessing new types of excitations and damages from a reliability perspective. This paper investigates a solution to enhance Printed Circuit Board (PCB) reliability within automotive Power Electronic Units (PEUs). Controlling vibration levels is crucial to prevent component breakage and PEU failure. The proposed approach exploits Locally Resonant Metamaterials (LRMs) to reduce PCB vibrational loads. LRMs provide excellent Noise, Vibration, and Harshness (NVH) performance within specific frequency ranges while being lightweight and providing high design freedom. Since direct integration into the PCB is unfeasible, the aluminum spider frame securing the PCB is treated instead. Previous simulations demonstrated significant vibrational load reduction. In this study, the LRM solution is fabricated, and experimental validation is performed using a shaker test mimicking operating conditions. Multiple configurations are explored: two concepts tuned to individual PEU resonance frequencies, and a hybrid configuration targeting both peaks simultaneously. Finally, relative damage is calculated using experimental data, comparing configurations with and without the LRM solution, demonstrating how this method can evaluate the LRM solution's performance in such applications.
Tincani, SaraClaeys, ClausDeckers, ElkePandiya, NimishDindorf, Christian
The EU funded innovation project High-Voltage fast-charging Efficient electric vehicle Powertrains (HiVEP) develops innovative technologies for mass-market electric vehicles (EVs) by advancing architectures operating above 800 V. These architectures integrate silicon carbide (SiC)-based power electronics, rare-earth-free electric machines with active winding reconfiguration, high C-rate batteries, and optimized thermal management systems. HiVEP aims to enable fast charging in less than ten minutes, reduce energy consumption by at least 25%, extend the driving range by 20%, and cut system costs by up to 20% in volume production. This article deals in detail with the project objectives, the methodological approach, and the expected key innovations, as well as the technical, environmental, and social impacts. The discussion situates HiVEP within the European research and innovation landscape, emphasizing its role in accelerating adoption of sustainable mobility solutions.
Schernus, ChristofNada, ShadyNeuhaus, ChristophEwald, JensSwierc, DanielKallur-Krishnamoorthy, RajeshVasiliadis, Harilaos
Aircraft lighting systems play a vital role in ensuring operational safety, visibility, and regulatory compliance. Exterior lighting systems are essential for aircraft identification, navigation, collision avoidance, and ground operations under varying environmental conditions. These systems typically include navigation lights, anti-collision lights, landing and taxi lights. An aircraft lighting system comprises light sources, optical elements, electronic control units, power interfaces, wiring harnesses, and mechanical mounting structures. Among these components, optics are critical as they control light distribution, intensity, color accuracy, and efficiency while withstanding harsh aerospace environments such as vibration, thermal cycling, and aerodynamic loads. Aircraft exterior lights are subjected to severe thermo-mechanical stresses due to aerodynamic loading, vibration, and thermal cycling. The use of high-performance optical polymers such as Cyclo Olefin Polymers (COP) provides excellent light transmission and stability; however, their relatively lower mechanical toughness makes them susceptible to stress-induced cracking during assembly. In the baseline configuration, the Circuit Board Assembly (CBA) was fastened directly onto the optic using self-tapping screws. During assembly, frequent crack initiation was observed in the optic around the fastener locations, leading to concerns regarding reliability and maintainability. To address this issue, a redesigned mounting approach was developed that eliminated direct fastener penetration into the optic. Instead, the CBA is retained using a precision clamping mechanism, thereby distributing assembly loads uniformly and avoiding localized stress concentrations. COP material was retained due to its superior optical characteristics and compliance with photometric requirements for aircraft lighting applications. The redesigned optic-CBA interface was validated through Highly Accelerated Life Test (HALT), incorporating combined vibration, temperature, and thermal shock profiles. Test results confirmed that the new clamping design prevented crack formation, improved mechanical robustness, and ensured long-term optical performance. This paper presents the problem definition, root cause analysis of fastener-induced cracking, the design rationale for adopting a clamp-based mechanism, and detailed HALT validation results. The study highlights the importance of integrating material properties, fastening strategies, and environmental testing in the design of aerospace lighting systems. The proposed design methodology provides a pathway to enhance reliability and lifecycle performance of critical optical components in aircraft applications.
Vialta, FredericoS, NikhilKatageri, PraveenSP, PradeepSingh, Abhimanyu Kumar
This study presents a torque distribution strategy for dual-motor electric vehicles utilizing a Deep Deterministic Policy Gradient reinforcement learning algorithm designed to optimize energy consumption. By using a simplified architecture and replicable reward functions, the proposed agents rely exclusively on standard CAN bus signals, commanded longitudinal force, and the motors’ velocities, eliminating the need for specialized sensors or complex plant models. Two reinforcement agents are trained using two different reward functions: power-based and State of Charge-based. These agents are validated through high-fidelity CarSim–Simulink co-simulations across soft, medium, and severe acceleration scenarios, in which they demonstrate superior performance to traditional adaptive methods. In the most demanding scenario, a typical adaptive strategy achieves an additional 7.8% of power consumption and 85% of optimal energy recovery, while the proposed reinforcement learning strategies reach 0.6% more consumption and 95% energy recovery during braking compared to the theoretical optimum. These results highlight a practical, reliable solution for maximizing efficiency in dual-motor powertrains without significant computational burden on existing electronic control units.
Meléndez-Useros, MiguelViadero-Monasterio, FernandoLópez-Boada, María JesúsLópez-Boada, Beatriz
Efficient thermal modeling is essential for the design and reliability of power electronics systems, particularly under fast transient operating conditions. Building upon prior formulations of the Lumped Parameter Linear Superposition (LPLSP) method, this work introduces an ensemble parameter estimation framework that enables reduced-order thermal model generation from a single transient dataset. Unlike the earlier implementation that relied on multiple parametric simulations to excite each heat source independently, the proposed approach simultaneously identifies all model coefficients using fully transient excitations. Two estimation strategies namely two-stage decomposition and rank reduction are developed to further reduce computational cost and improve scalability for larger systems. The proposed strategies yield models with temperature-prediction errors within 5% of CFD simulations while reducing model development times from O(103 s) to O(100 s)–O(101 s). Once constructed, the model evaluates new transient operating conditions in O(100 s), enabling rapid thermal analysis and enabling automated generation of reduced-order models for both simulated and physical systems. These advancements significantly accelerate early stage design iterations and mission-profile evaluations for thermal management of electronic systems.
Padmanabhan, Neelakantan
Deep Reinforcement Learning (DRL) for quadrotor flight control typically relies on Domain Randomization (DR) for sim-to-real transfer, resulting in overly conservative policies that struggle with dynamic disturbances. To overcome this, we propose a novel adaptive control architecture that actively perceives and reacts to instantaneous perturbations. First, we train an optimal outer-loop policy, then replace its reliance on ground-truth disturbance data with a Residual Dynamics Predictor (RDP). The RDP estimates the external forces and moments acting on the aircraft in flight online using only the history of states and control actions. For seamless hardware transfer, we introduce a data-efficient linear calibration bridge and an online thrust correction mechanism that align the simulated latent space with reality using mere seconds of flight data. Real-world validations on a Crazyflie micro-quadrotor demonstrate that our adaptive controller significantly outperforms baselines, maintaining precise trajectory tracking under severe uncertainties including mass variations, asymmetric payloads, and dynamic slung loads.
Saj, VishnuBenedict, MobleKalathil, DileepVemuri, Sushil
This paper presents the integration and validation of Adaptive Cruise Control (ACC) algorithms on a student-team-developed vehicle as part of the U.S. Department of Energy EcoCAR EV Challenge. The competition provided each team with a 2023 Cadillac Lyriq, which was modified to an all-wheel-drive configuration and re-architected to support the development of SAE Level 3 autonomous features including Adaptive Cruise Control (ACC), Automatic Intersection Navigation (AIN), Lane Centering Control (LCC), and Automatic Parking (AP). The scope of this paper, however, is limited to the development, implementation, and validation of a Level 2 longitudinal ADAS function. Higher-level automation requirements such as Operational Design Domain (ODD) definition and Driver Monitoring System (DMS) enforcement are addressed at the vehicle architecture and competition level but are not the focus of this work. The major contribution of this work is the development of ACC with Vehicle-to-Infrastructure (V2I) integration, highlighting the end-to-end implementation of the ACC algorithm and its interaction with key actuation systems in the modified vehicle architecture. The ACC algorithm encompassed multiple applications: conventional cruise control to maintain speed, adaptive cruise control to respond to a lead vehicle, and initial deceleration handling for intersection navigation in a single straight lane. By implementing a unified algorithm, transitions between these modes were smooth and more efficient compared to developing separate algorithms for each application. Track-based testing and calibration were conducted to validate these modes under real-world scenarios, ensuring safe operation while addressing the challenges of blended actuation. Multiple track tests were used to measure stopping distances at intersections for different entry speeds, evaluate controller performance during different driving scenarios, and identify system limitations. Results demonstrated that the controller maintained steady-state speed error within +/- 1 km/hr, preserved a minimum following distance of 8 m at a complete stop, and limited acceleration within +/- 2 m/s2 to support driver comfort. The work demonstrates the progression from simulation to real-world deployment using an empirical approach to system-level validation of ACC with V2I integration. The findings provide insights into calibration methodology, mode transition, and the benefits of a unified control framework for advancing software-defined vehicle features.
Gupta, IshikaEstrada, TylerTambolkar, PoojaMidlam-Mohler, Shawn
Electronics is entering rapidly into all automotive subsystems, performing control and monitoring tasks apart from making the entire vehicle intelligent. Interface with the external automotive eco-system needs careful attention during the system design. It defines how seamlessly the electronic unit interacts with rest of the vehicle. It needs to do so in an effective manner without compromising on cost and other automotive application constraints. This paper focusses on the “smart switch building block” that forms heart of an automotive output interface echo system.: Its importance stems from the fact that, a smart switch is an indispensable building block for any electronic control system driving external loads. As various novel electical and electronics architectures are entering various vehicle segments, the need for a single reusable solution that will cater to 12 Volts to 48 Volts battery buses is increasingly being felt. However, no prevelant solution meets this requirement. Even for 12 volts and 24 volts buses different solutions are sometimes required to be used. Other areas where the existing solutions need improvement include ease of hardware and software interface apart from lack of robust short-circuit protections. Diagnostics architecture of currently available (legacy) smart switch solutions add to the complexity of the interface for interpretation of the malfunctions. This paper proposes a novel architecture that attempts to address all these short-comings across the buses. This not only reduces the time to market but also reduces engineering and Bill of Material (BOM) costs due to a frugally engineered solution.
Vaidya, Vishwas Manohar
Improving the energy efficiency of electrified vehicles remains a central objective in modern electric powertrains. Multi-level converters (MLCs) are widely recognised for lowering conversion losses relative to two-level inverters and improving total harmonic distortion (THD) in the sinusoidal supply to motors with a consequent reduction in motor losses. Despite this, sustained production-oriented validation at the integrated system level remains limited. This work introduces a multi-level converter architecture of the Battery Integrated Modular Multi-Level Converter (BIMMC) topology using Cascaded H-Bridge (CHB) architecture. It offers improvements in all key metrics of performance, cost, package size, mass and robustness compared to the current state-of-the-art two-level inverter system with distributed functions for charging available in the market today. The overall solution is highly functionally integrated. It supports four major functions required in electric vehicles without the need for additional hardware. Firstly, supply to and control of a three-phase electric motor without the need for a separate, standalone inverter. Secondly, all usual battery management system (BMS) functionality including energy and State of Charge (SOC) management to module level enabling usable energy and robustness improvements. Thirdly, the ability to charge from both alternating current (AC) (single phase and three-phase) and direct current (DC) sources without the need for separate on-board charger (OBC) hardware whilst also enabling an innovative pulse charging approach which benefits both charging time and battery ageing compared to conventional DC charging. Finally, the ability to deliver a controlled DC supply to non-traction loads on the vehicle with high efficiency and redundancy. The BIMMC topology proposed has been designed, built at prototype level and tested in order to collect performance data to empirically validate empirical study of the performance and functional benefits of the approach for traction motor drive, battery stored energy management and charging. Measured results demonstrate that improved inverter waveform quality correlates with lower motor harmonic losses and measurable drive-cycle efficiency gains, consistent with prior MLC assessments. Battery SOC depletion can be managed actively within the complete battery yielding increased usable energy and further driving range gains. Pulse charging shortens charge time whilst maintaining battery health metrics within acceptable limits, aligning with experimental evidence on pulse-based fast charging. The topology has also demonstrated the ability to pulse charge cells in a complete battery pack whilst consuming incoming DC supply current from a standard commercially available DC charger (Electric Vehicle Supply Equipment - EVSE). This potential to offer the benefits associated with pulse charging without requiring change to existing deployed charging infrastructure. Overall, proposed CHB-BIMMC architecture offers a practical blueprint for next-generation electric vehicles (EVs), and is compatible with ongoing integration trends that converge traction, charging and battery management functions within a unified power electronics and control platform.
Bao, RanKalaiselvan, PrashanthRener, KristofHallam, PhilipShi PhD, KaiYue, WilliamMa, HeGrimshaw, AndrewPatel, Simon
In the stringent market of BEV, the development of integrated Drive Modules (iDM) fitting environmental and customer needs is mandatory. It is important to extract the best from the less. To achieve those goals, a deep insight into complex multiphysics phenomena occurring in an iDM has been achieved by accurate and validated models. This engineering methodology is applied through the development of BorgWarner products, comprising non-exhaustively iDM 180-HF, Externally Excited Synchronous Machine and Multi-Level Inverter. The paper will review the methodology development for deeper understanding involving in-house technical excellence and complemented by strategic partnerships with academic institutions and start-ups. It will present the approach of integrating advanced multiphysics models with high-quality experimental validations, specifically on loss evaluation on electrical machines and inverters. Complex models involving multiphysics such as thermal/fluid coupling or electric-magnetic-mechanical behaviors are usually difficult to optimize separately since their objectives are often contradictory. Thus, BorgWarner PDS Engineering uses tools involving close coupling to optimize iDM products. The lecture will focus on innovation and optimization which are supported by several key pillars in the scope of a Next Generation iDM development. These are based on the following strategic levers such as process and design development, material development and control strategy among others. This ensures tailoring all components at the best of their capabilities to reduce their weight and maximize their use. Finally, the results achieved by the high-fidelity model-based optimization on the selected example will be presented (e.g., impact of the cooling improvement on overall iDM performances), demonstrating the benefit of capturing the system from granular view to a helicopter view in the design phase of next generation eDrives.
Leblay, ArnaudBourniche, EricBossi, AdrienDavid, PascalNanjundaswamy, Harsha
The design and development of EVs and HEVs has become a growing issue recently due to concerns about pollution and dependence on non-renewable fossil fuels. Accordingly, General Motors (GM) has an evolving vehicle electrification plan over the past several decades and into the future to deliver low-cost and efficient EVs and HEVs. Propulsion system requirements for the applications of EV and HEVs are quite different and therefore, the design principles and directions are also distinct between these cases. From micro-hybrid and full plug-in hybrid applications to full EV applications, design requirements, strategies and outcomes can widely vary. Continuous and peak duty are substantially different depending on the application of the vehicle. Motor operational duty is significantly higher for EV compared to the electric motor of a hybrid electric vehicle. Motor torque, power and efficiency requirements are also higher for EV motors, which greatly influences the choice of motor type and its thermal and electromagnetic design. Issues like NVH and thermal can be less significant in designing motors for HEV because of engine masking and lower duty cycle of operation. Motor design requirements, optimization process and results for two different motors intended to be used in EV versus HEV applications are discussed in this paper. Moreover, traction inverter requirements differ significantly across electric vehicles and various hybrid architectures. Each configuration presents distinct challenges—ranging from packaging and thermal management to vibration and electrical constraints. Despite these differences, the design and requirements are harmonized to reduce complexity and ensure seamless performance. This paper outlines the design strategies employed to achieve these objectives.
Momen, FaizulJensen, WilliamDas, ShuvajitChowdhury, MazharulAlam, KhorshedAnwar, MohammadReinhart, Timothy
In recent years, the use of software-defined platforms has become increasingly prevalent. As a result, flashing ECUs has become an important factor in ensuring efficiency, quality, and compliance in vehicle production. Conventional approaches, such as final end-of-line flashing, are increasingly unsuitable for the growing amounts of data, complex dependencies, mixed physics and protocols, and traceability requirements. This SAE paper presents the current trends and challenges in ECU flashing. It highlights the impact of the exponential growth in software payloads and the necessary migration to offline and parallel workflows. This can only be achieved through closer integration with automated and robot-assisted production, considering the requirements of cybersecurity and verifiability. It also addresses the shift toward end-to-end flashing ecosystems, where updates are performed consistently from a single source covering the assembly line, warehouses, yards, workshops, and over-the-air updates. By comparing old and new approaches to high-speed flashing and presenting a new flashing strategy for OEMs derived from this, the paper provides a framework for understanding the future of ECU flashing on its way to software-defined mobility.
Böhlen, BorisBudak, OguzWells, Michael
The objective of this paper is to understand the effort required to integrate the hardware and software of in-vehicle cybersecurity systems. The in-vehicle cybersecurity method discussed is the SAE J1939-91C, which involves Network formation, Rekeying, and secure Message Exchange between Electronic Control Units (ECUs). The SAE J1939-91C network security protocol operates over a CAN-FD network to perform necessary cryptographic operations and key generation. To evaluate the method, test vectors were created to validate SAE J1939-91C key generations and cryptographic operations on the simulated ECU in-vehicle network system hardware (such as the Beacon or Pi devices). We introduce a lightweight, transport-agnostic benchmark comprising deterministic AES-CMAC test vectors and a simple verification utility, requiring no specialized hardware or build system. This minimal artifact set enables reproducible and machine-parsable validation of SAE J1939-91C security across diverse lab environments.
Zachos, MarkMedam, Krishna Teja
Heavy-duty electric trucks represent a growing innovation in the transport and logistics sector, aiming to reduce emissions and reliance on fossil fuels. A major challenge with battery electric trucks is the long recharging time which takes significantly longer than refueling conventional diesel trucks. This limitation highlights the importance of optimizing powertrain operations to reduce energy losses and maximize efficiency. One effective approach is implementing optimal speed control through a predictive cruise controller. By anticipating road conditions, traffic, and elevation changes, the predictive cruise controller can adjust the truck’s speed in real time to minimize energy consumption, enhancing the range and reducing the need for frequent charging. Many problem formulations for electric trucks focus primarily on minimizing the energy required at the wheels, often overlooking the impact of powertrain efficiencies. This simplification neglects critical factors such as the efficiency of the traction electric machine (EM), gear losses, and battery dynamics, which are essential for optimizing overall energy consumption and improving vehicle performance. This research paper shows the impact of powertrain efficiencies on the optimal speed profile generation with a predictive cruise controller (PCC). The PCC optimizes electric truck operation by focusing on three primary factors in its cost function: 1) battery energy consumption, 2) total trip time, and 3) battery state of charge (SOC). To achieve the optimal speed profile, Sequential Quadratic Programming (SQP) is used. A comparison was made with a conventional cruise controller, which simplifies the vehicle model by minimizing the required energy at wheels and ignores powertrain losses in its energy calculations. The results show that the proposed PCC offers a 12.85% improvement in battery SOC and 10.83 % improvement in energy consumption as compared to baseline.
Safder, Ahmad HussainVillani, ManfrediKhuntia, SatvikNelson, JamesMeijer, MaartenAhmed, Qadeer
An on-road study has been conducted where a modern vehicle with a 3L turbocharged, PFDI gasoline engine was upfitted with appropriately sized uncoated GPFs for soot capture in a dual-bank exhaust line. The tested GPFs, whether clean or pre-loaded, were weighed to track their soot-load trends between representative real-world driving routes, where sensor data and exhaust temperature data was recorded. Thus, characterization of the passive soot regeneration process in the uncoated GPF was linked to elevated temperatures and vehicle drive cycles speeds.
Craig, AngusWarkins, Jason
Automotive Original Equipment Manufacturers (OEMs) closely guard information about their products due to the significant investment in vehicle research and development. However, advancing automotive innovation often requires insights from existing systems to improve safety, efficiency, and performance. The Controller Area Network (CAN) bus remains the industry standard for communication between electronic control units (ECUs), yet CAN message specifications are typically proprietary and undocumented. This paper presents a case study involving the reverse engineering of CAN messages from a 2024 Toyota Grand Highlander powertrain. By capturing and analyzing communication between a diagnostics tester and the vehicle’s ECUs and replicating the communication, substituting A CANcase and software in place of a diagnostics tester, we were able to reverse engineer the vehicle’s CAN bus, demonstrating a practical methodology for decoding and interpreting CAN traffic without prior access to proprietary data. The approach highlights both general principles and OEM-specific variations in message structure and encoding. The goal of this work is to support researchers and engineers in developing their own reverse engineering workflows. It illustrates that while the foundational techniques are consistent, adapting to vehicle-specific implementations is essential. The paper aims to provide a replicable process and to encourage further exploration in the field of automotive CAN analysis.
Bolarinwa, EmmanuelPeters, Diane
Demand for cost-effective automotive traction inverters requires improved power module packaging. This paper presents a packaging method using an epoxy composite insulator applied directly to the cold plate surface, replacing Direct Bonded Copper (DBC) and Active Metal Brazed (AMB) substrates. This integration removes the substrate-to-cold plate solder interface and eliminates two material layers from the thermal path. The epoxy composite demonstrates a dielectric strength greater than 60 kV/mm. Thermal resistance (junction-to-coolant) measured approximately 0.17 K∙cm2/W. Electrical characterization showed a relative permittivity of 3.9, which is lower than standard ceramics and results in reduced parasitic capacitance. Initial thermal cycling tests indicated no significant degradation in thermal or electrical performance. These results suggest the epoxy composite insulator could be a promising alternative for traction power modules.
Chen, YuMena-Garcia, JavierChen, HaoXiao, KeweiGupta, Man PrakashDegner, Michael
Accurate control of the engine park angle during Autostop in hybrid vehicles is critical for enabling rapid and smooth Autostarts, reducing start-up vibrations, and enhancing overall driving comfort. However, in real-world scenarios, the available torque for engine positioning is often limited by competing driver torque demands, battery discharge constraints, and the state of charge (SoC). Under these conditions, conventional position-speed control strategies frequently fail to achieve the desired precision. This paper introduces an adaptive control strategy for the electric machine (EM) that drives the internal combustion engine, ensuring precise alignment of the crankshaft at a predefined angle to optimize restart conditions. Upon receiving an engine shutdown request, the proposed controller computes an adaptive deceleration profile that respects the EM’s torque and deceleration limits while guiding the crankshaft toward the target park position. The core of the approach lies in generating a theoretical speed trajectory and tracking it through an adaptive nonlinear control law that dynamically adjusts in real time to compensate for disturbances and eliminate residual angular error at the end of the maneuver. Unlike conventional methods, the proposed solution maintains robustness under stringent deceleration constraints and varying operating conditions. Simulation and experimental results on a hybrid powertrain test bench demonstrate that the proposed method significantly improves park angle accuracy and consistency even under limited deceleration scenarios.
Purohit, PunitAchir, AliBhakare, Allwyn
This paper proposes an intelligent, artificial intelligence (AI) enabled seat heating system for school buses that saves energy by only activating heating elements when a passenger is identified. A custom-trained YOLOv8 deep learning model identifies passengers in real time and opens/closes real-time control of the individual electric seat heaters via a Raspberry Pi 5. The detector achieves around 10 frames-per-second (FPS) of inference on the Raspberry Pi 5 and 80–90 FPS on a laptop with over 92% detection confidence across various illumination conditions. Energy modeling shows the anticipated demand for a 10-kW propane-based heater is approximately 75% lower by implementing a 2.52 kW electric seat-heating system. In a typical operation schedule of 540 hours a year, this results in 4,000–5,000 kWh of annual savings, $465–$579 of annual cost savings and mitigates 0.9–1.3 t CO₂ per bus, annually. When implemented at the fleet level, the energy and cost saving will be in proportion. This approach offers a cost-effective, modular, and safe electrified public transportation solution that integrates comfort optimization with environmental accountability.
Chikkala, Daney BhargavZadeh, MehrdadTan, Teik-KhoonPonnam, JitinBatte, Jai Rathan
Conventional inverter control uses a fixed switching frequency, which leads to high-pitched switching noise in electric vehicles (EVs) that does not vary with vehicle speed. Although EVs are much quieter than traditional internal combustion engine (ICE) vehicles, some EV owners complain about the lack of dynamic driving sound feedback. A new patented technology has been developed to enhance EV sound quality by dynamically controlling the inverter switching frequencies. This technology generates dynamic propulsion sound with new "switching order" features at multiple harmonics, with the pitch proportional to vehicle speed. A constant pulse ratio between the switching frequency and the electric motor RPM is implemented to control the switching order. This reduces switching losses during low-speed operation and provides boosted acoustic feedback to the driver during acceleration, which enhances driving experience during sports driving. Furthermore, a special "EV shifting" sound that mimics the sound of gear shifting is generated by controlling different pulse ratios at each shifting RPM zone. High switching orders are dropped between neighboring zones to boost lower frequencies for an enhanced dynamic driving experience. These new switching sound features have been validated through electric drive unit and electric vehicle tests. Jury tests confirm the new EV sound with switching orders is authentically generated from electric propulsion system and can be tuned by controlling the switching pulse ratio. This technology has been successfully implemented in the "Watts-to-Freedom" drive mode of the Hummer EV, providing enhanced EV sound feedback, and improving the driver's experience during high-acceleration events.
He, SongGagas, BrentWelchko, BrianBall, KerrieGong, Cheng
This paper explores the application of an Improved Enhanced-Boost Quasi-Z-Source Inverter in AC-connected extreme fast charging (XFC) stations for electric vehicles (EVs), aiming to reduce conversion stages and enhance system efficiency. AC-connected XFCs offer superior reliability compared to DC-connected systems due to better fault tolerance and reduced sensitivity to power fluctuations but traditionally suffer from increased complexity and reduced efficiency due to multiple conversion stages. The proposed inverter addresses this by combining DC-DC and DC-AC conversion into a single stage, simplifying the system, decreasing losses, and improving efficiency. Furthermore, this research investigates the use of Spiking Neural Networks (SNNs) for generating the precise pulse width modulation (PWM) signals required for the Quasi-Z-Source Inverter. SNNs offer potential advantages in terms of dynamic response and adaptability compared to traditional PWM techniques, allowing for optimized inverter control under varying load conditions. By operating at a higher modulation index, the inverter reduces switch stress, making it suitable for high-power applications. Analytical results and simulations demonstrate the inverter's potential, enhanced by SNN-based pulse generation, in advancing next-generation fast charging solutions by simplifying infrastructure and improving charging efficiency, positioning it as a promising technology for the future of electric vehicle charging.
Saliesh, DileepSanaboyina, PrudhviChhagar, RohnitsinghSatyanarayan, Swapna
Complexity of modern ground vehicles grows constantly, since car manufacturers want to provide functionality, while customers are expecting innovation and recent technologies to be integrated into the latest models released to the market. Recent advances in hard- and software opened the gates for new means of vehicle control and operation. Especially the transition to electric propulsion systems and decoupled chassis actuators offer completely new opportunities of dynamics control and manipulation. This paper presents an approach for integrated chassis and vehicle motion control in (battery) electric vehicle applications by using new and innovative controllers as well as mechatronic chassis systems. In several experiments on public roads with a fully instrumented vehicle demonstrator, that features in-wheel based rear-wheel drive and a hybrid brake-by-wire-system, the proposed control is tested under real environmental and traffic conditions with respect to aspects like energy efficiency and driving comfort. The improvements are evaluated by objective performance indicators. In particular, it was found that the controller recovers more kinetic energy during braking maneuvers and lowers driver stress by up to over 90 % fewer mandatory pedal changes compared to already industrialized approaches.
Heydrich, MariusMitsching, ThomasIvanov, Valentin
Accurate flux linkage characterization is essential for the design, control, performance and efficiency optimization of permanent magnet (PM) traction motors in automotive applications. Precise knowledge of flux linkage across varying load, speed, and temperature conditions directly impacts torque production, field-weakening capability, overall drive system efficiency and torque security. This paper presents a critical review and classification of flux-linkage characterization methods, encompassing offline laboratory mapping, standstill signal injection, self-commissioning inverter-only routines, and online real-time estimation. Each method exhibits distinct trade-offs in terms of accuracy, robustness to inverter nonlinearities, temperature adaptability, cost, and scalability for production and in-vehicle use. With the increasing complexity of automotive traction systems, understanding these trade-offs is crucial for optimal motor design and control. To enable systematic comparison, a performance evaluation framework is introduced based on key performance indicators (KPIs), including accuracy (below base speed, field weakening, and regeneration conditions), robustness to stator resistance variations and inverter nonlinearity, thermal adaptability, test complexity, time efficiency, cost, and applicability across the motor development lifecycle. These KPIs were selected based on their direct impact on motor performance, manufacturability, and suitability for various stages of automotive traction motor development, ensuring that analytical, dyno testing, and in-vehicle considerations are addressed.
Khan, Ahmad ArshanHaddad, ReemonKim, JayHermann, JustinMohamadian, Mustafa
Negotiating Keys for applications such as message authentication within a vehicle presents many problems as, in designing the algorithm; the algorithm must be able to be utilized by small, fixed-point processors. In addition, if there is a desire to do this algorithm in the manufacturing environment, there are severe time constraints placed on how long this algorithm can take, as there are strict station time requirements, which are expensive to change, and any time utilized in the plant can negatively affect vehicle throughput. Additionally, negotiating these keys between many ECUs can greatly increase the time required to negotiate a common key using standard multi-party Diffie-Hellman. Timing would also be an issue in the case of using pair-wise Diffie-Hellman for encryption and distribution of keys utilizing a key master. To solve these problems in multi-party key negotiation, we have utilized the Elliptic Curve variation of the Burmester-Desmedt (ECBD) algorithm. ECBD is relatively fast for a large number of ECUs, though the primary benefit of utilizing this algorithm is that calculation times for key negotiation vary only slightly for a wide range of number of participants. This enables the easy planning of negotiation time based on the number of keys the vehicle requires without worrying about the number of ECUs that require each key. This approach also has advantages over key injection and direct key distribution schemes because it does not require a secure environment at any point in the process. Thus, ECBD can be implemented without a secure clean room in either the manufacturing or maintenance environments. This is especially valuable in the maintenance environment, as it enables easy compliance with right to repair laws without endangering vehicle cyber security.
Van Dam, TheoMazzara, Bill
Software-defined vehicles (SDVs) are reshaping automotive control architectures by shifting intelligence to embedded systems, where computational efficiency is paramount. This paper presents a systematic evaluation of control strategies (PID, LQR, MPC) for the classical control problem involving inverted pendulum on a cart under strict embedded constraints representative of software-defined vehicle ECUs. The objective is to evaluate and compare the performance of advanced control algorithms under varying control objectives when deployed on microcontrollers with constrained computational and memory resources, representative of the limitations encountered in embedded platforms used for SDVs. Furthermore, the study illustrates systematic optimization strategies that enable these algorithms to achieve real-time execution within such resource-constrained environments. Each control strategy is implemented with careful consideration of algorithmic complexity, real-time responsiveness, and resource utilization. Performance is evaluated across key metrics, enabling a comparative analysis that highlights trade-offs between control fidelity and hardware efficiency. By demonstrating how advanced control logic can be effectively deployed on constrained hardware, this work supports the broader goal of enabling intelligent, responsive vehicle behavior through software-centric design. The findings are particularly relevant for automotive and embedded engineers developing control systems for SDVs, where balancing performance and resource constraints is critical to achieving scalable, safe, and adaptive vehicle functionality.
Vupparige, VarunPandya, Vidit
Inverters are typically integrated into electric drive units for electric vehicles (EVs) to reduce packaging size and cost. However, coupled vibrations from the electric motor and gears are transmitted to the inverter, which can become a dominant noise source due to its large radiative panel. Metal panels are required for electromagnetic interference (EMI) compliance, yet these covers usually lack sufficient stiffness or damping for noise control. Adding ribs and applying damping treatments result in excessive mass, cost, and packaging challenges. A new bubble sheet panel design has been developed to enhance the structural strength and damping performance of the inverter cover while significantly reducing its mass. A thin sheet of aluminum is welded onto the cover in an optimized pattern that enhances stiffness and damping performance while accommodating packaging requirements. The welding pattern can include logos or artistic designs to improve the panel’s appearance. The metal sheets are blown apart between the welds to form a 3D structure that is three times stiffer and twice as strong as a flat monolithic sheet of the same thickness. The composite dual bubble sheets can effectively reduce structural vibration. Damping materials, such as liquid-applied sound deadener (LASD), can be injected into the bubble sheet cavities to significantly improve its damping performance. Prototype bubble sheets have been designed, analyzed, and tested for an integrated inverter used in front-wheel-drive (FWD) electric drive unit for EV applications. Analysis and modal tests show a reduction of 10 to 15 dB at panel resonances with close to 30% reduction in mass. The bubble sheet panel is installed on an integrated inverter and tested in the electric drive unit. Sound power measurements confirm a reduction of up to 10 dB in inverter panel vibration.
He, SongBobel, AndrewNaismith, GregoryYi, WenwenPatruni, Pavan Kumar
This paper describes a systematic approach to evaluate lubricants for hybrid and electric vehicles (xEVs) that can detect impacts on efficiency as low as 0.1 percentage points. Two testing methods were developed to evaluate lubricants’ efficiency effects: (1) on a complete vehicle (using the manufacturer’s hardware and motor control) and (2) on a standalone drive unit (using custom power electronics and control). A Monte Carlo simulation was used to analyze the resulting data to determine the detection limits of the vehicle test method. To evaluate the effectiveness of the test stands and the data-analysis method, a Tesla Model 3 electric drive unit and a Chevrolet Bolt battery electric vehicle (BEV) were characterized for system efficiency. For the Bolt mounted on a hub driven chassis dynamometer, this method is capable of detecting a change in the drive unit’s electromechanical efficiency between baseline and candidate fluids of <0.4 percentage point (pp) with 95% confidence at most of the operating points analyzed. This method can be applied to high-precision testing applications, such as lubricants or additives, cooling systems, gear trains, dynamic seals, bearings, or electric motor designs.
Luo, YilunGross, MichaelKostan, Travis
The emergence of AI-driven autonomy in modern vehicles marks a pivotal evolution in transportation, but it also introduces deep system-level vulnerabilities that span from sensor interface tampering to compute unit compromise and untrusted communication links. Autonomous vehicles (AVs) operate as distributed intelligent systems, relying on real-time data exchange between zonal gateways, AI compute platforms, and safety-critical electronic control units (ECUs). These interactions must be protected from hardware-based attacks that could compromise functional safety, system integrity, or operational availability. The deployment of AI-driven AVs introduces unprecedented levels of complexity. Sensors, AI compute clusters, and actuators communicate over multiple interfaces including Ethernet, PCIe, and MIPI, exposing vehicles to potential cybersecurity attacks. This paper proposes a unified, layered hardware security architecture tailored for AI-powered automated vehicles. Grounded in current automotive Ethernet and zonal architectures, it provides end-to-end trust using hardware interface security, accelerated- cryptography, and SRAM PUF-based key provisioning. All security primitives are anchored to hardware root of trust, delivering cryptographic identity, secure boot enforcement, and trusted key storage across the entire vehicle lifecycle.
C Suriyanarayanan, PavIacob, Radu
General Motors (GM) continues to advance its electrification strategy through the development of scalable Battery Electric Vehicle (BEV) and Battery Electric Truck (BET) platforms. This paper highlights GM’s latest BEV and BET products that leverage shared Drive Unit (DU), Rechargeable Energy Storage System (RESS), and integrated power electronic (IPE) components across multiple vehicle programs. By adopting a modular and commonized propulsion architecture, GM achieves significant benefits in manufacturing efficiency, cost optimization, speed to market, and product flexibility. The shared DU, RESS, and IPE components are engineered to meet diverse performance requirements while maintaining high standards of energy efficiency, thermal management, and durability. This approach enables rapid deployment of electrified solutions across various segments, from passenger vehicles to full-size trucks, without compromising on capability or customer experience. The paper outlines the technical rationale behind component commonization, including design considerations and integration challenges. Through this shared architecture, GM demonstrates how intelligent component reuse can accelerate innovation, reduce complexity, and support the transition to a zero-emissions future. The findings presented offer valuable insights into the role of scalable propulsion systems in shaping the next generation of electric mobility.
Liu, JinmingSevel, KrisAnwar, MohammadOury, AndrewWelchko, BrianGagas, Brent
Flow simulation with conjugate heat transfer, which involves fluid flow, conduction, and radiation within solid components, is a vital capability that enables engineers to design and assess cooling systems for heat-producing parts such as brakes, powertrains, batteries, and power electronics in both gasoline and electric vehicles. In this study, we employ PowerFLOW®, which features a thermal solver capable of simultaneously modeling both fluid and solid domains within a unified framework. The fluid flow is simulated using the Lattice Boltzmann Method (LBM) with VLES turbulence modeling based on the RNG k–ε approach. The solid domain is solved using a finite volume method with second-order accuracy for thermal conduction, combined with surface-to-surface radiation modeling for thermal exchange between surfaces. This integrated approach streamlines the simulation workflow while enabling accurate representation of both conduction and radiation phenomena. We assess the accuracy of the conjugate heat transfer (CHT) simulation methodology for both forced and natural convection benchmark cases. For the forced convection case, channel flow with heated mounted cubes was analyzed, while for the natural convection case, a simplified engine bay under soak conditions was simulated. In both configurations, the simulation results showed good correlation with experimental data, demonstrating the reliability of the CHT approach.
Mukutmoni, DevadattaShock, RichardLi, HanWanderer, JohnGopalaswamy, NathMiao, Ling
Floating-point arithmetic is widely used in automotive embedded software to scale Controller Area Network signals and calibration parameters with fractional factors such as 0.1. However, floating-point operations, even on microcontrollers equipped with floating-point units, can increase execution time and CPU load. In AUTOSAR architectures, converting floating-point scaling to fixed-point is not trivial because scaling semantics must be integrated consistently across components, yet AUTOSAR platform toolchains offer only limited automation at the Application Data Type level. Although CompuMethod definitions can express scaling, integration typically remains manual and distributed across application software components, reducing consistency and reusability. This study presents an architecture-driven methodology that formalizes fixed-point scaling as a centralized architectural service, realized through a parser-driven fixed-point macro generation pipeline. Standardized CAN DBC and calibration metadata are parsed to automatically generate integer-only macros for raw-to-physical and physical-to-raw transformations. The generated macros are integrated into dedicated AUTOSAR-compliant Scaling Service software components, consolidating scaling logic and improving reliability and maintainability. The approach requires no changes to toolchains, compiler settings, or hardware, enabling direct deployment in AUTOSAR-based software. The methodology was applied to a production-grade Integrated Charging Control Unit targeting Electric Vehicle Communication Controller software. Evaluation included cycle-accurate profiling, edge-based timing, isolated CPU load calculation, and average current measurement. Results show a 98.84% reduction in floating-point operations and a 92.67% reduction in conversion-related source lines. Task execution time decreased by 16.13%, CPU load decreased by 6.88%, and average current consumption showed a repeatable 0.81% reduction. These results demonstrate that the proposed methodology improves execution efficiency and is applicable to production AUTOSAR-based ECUs.
Lee, HoseokKo, Donggun
Mechatronic and cyber-physical systems emerge from interdisciplinary design efforts, integrating software (SW), electronics, and mechanical components. Developing such systems places high demands on organizations and processes, particularly regarding efficient collaboration across domains. A key challenge lies in establishing organizational structures and workflows which allow cross-discipline work and at the same time ensure compliance with regulations and adherence to standards such as Automotive Software Process Improvement and Capability Determination (ASPICE). In response, the authors have developed an Engineering Process Framework (EPF) grounded in International Council on Systems Engineering (INCOSE) systems engineering principles. The EPF provides a structured approach for system development and therefore defines company-wide processes and methods. This paper presents the development of the EPF’s functional logic and its implementation within a tool landscape. Furthermore, a selected process is used to illustrate how the EPF supports development engineers in their daily work.
Gehrt, Jan-JöranGranrath, ChristianCaglayan, EbruReckeweg, ThomasRichert, Felix
As already well-understood/enormous engineering practices, the inverter AC-side NVH phenomena/mechanisms/measures for motor-equipped vehicle, are already pretty clear. In addition to inverter AC side–induced NVH issues, DC ripple induced by PE switching leads to NVH issues manifesting on the capacitor, inductor, and conductor in terms of reverse piezoelectricity, electrostriction, magnetostriction, Laplace force, and so forth. These DC-side NVH issues are already literally analyzed by a couple of literatures, and mechanisms/measures are explored/applied to electric drive development. And yet, the phenomenon that a pulsating magnetic field inside a battery pack induced by DC current ripple off PE switching brings noise at switching frequency inside the vehicle cabin is newly captured/analyzed by our research, and that has been barely searched during the literature survey. This newly discovered phenomenon is the pivotal point in this paper. Although the noise features like the conventional switching noise that originates at the AC side of the inverter, the mechanism/measures are different; hence, this newly found NVH phenomenon is termed as alternative switching noise by the author, distinguishing itself from the conventional switching noise off AC side of the inverter. The mechanisms and measures associated with this phenomenon are innovatively explored/analyzed, which ultimately offer great aid to BEV/HEV/PHEV NVH interpretation/development. First, in this paper the inverter AC-side NVH issues are overviewed including mechanisms/measures, then DC-side NVH issues from capacitor, inductor, and conductor are reviewed in terms of mechanisms/measures, third the extending exploration/study upon alternative switching noise is described in detail. The relevant analysis for alternative switching noise is barely mentioned/involved during literature survey, and that is newly found/studied within the research delineated in this paper. Fourth, two case studies are exemplified to further validate the mechanisms/measures employed during investigation. In the end, the common strategies addressing the alternative switching noise are summarized, which shall be adopted to keep issues from happening at the very beginning of vehicle development stage.
Zhao, QianZhao, YihanNiu, HaolongLi, QiweiZhang, WenchaoXue, HongbinCheng, YananLi, JingKang, Ming
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