Search Results (400)

In response to the frequent safety incidents associated with the core electrical systems (i.e., traction battery, charging system, and drive motor) of new energy vehicles (NEVs) and the lack of forward-looking quantitative risk assessment methods in existing detection and diagnostic technologies, this study introduces the Layer of Protection Analysis (LOPA) methodology into the field of NEV safety. Unlike qualitative methods (e.g., FMEA, FTA) or purely data-driven diagnosis, this work establishes a tailored semi-quantitative LOPA framework that defines scenario-specific independent protection layer (IPL) identification criteria and probability of failure on demand (PFD) assignment rules for NEV applications. Typical risk scenarios, including battery thermal runaway, electrical faults in charging systems, overheating of drive motors, and battery internal short circuits caused by mechanical abuse, are systematically analyzed in terms of their failure mechanisms and evolution processes. A tailored quantitative risk assessment framework is established and applied to conduct full-process risk evaluations for the four scenarios. The results indicate that, under the synergistic effect of multiple protection layers—including inherently safe design, basic process control systems, safety instrumented systems, and physical protection measures—the accident consequence frequencies of all scenarios are significantly lower than the tolerable risk thresholds. This verifies the applicability and effectiveness of the LOPA method in NEV safety analysis. The proposed quantitative framework provides a scientific basis for safety design optimization, identification of critical protective elements, and operation and maintenance strategy formulation throughout the lifecycle of NEVs. Furthermore, the limitations of data portability from process industries are discussed, and sensitivity analyses are conducted to confirm the robustness of the conclusions. Full article

Driven by demanding global emission regulations and the urgent requirements for sustainable mobility, Electric Vehicles (EVs) have emerged as the primary alternative to Internal Combustion Engine (ICE) vehicles. Central to this transition is the electric propulsion system (EPS), a multidisciplinary integration of power electronics, advanced motor drives, and electrochemical energy storage. This paper provides a comprehensive overview of the current landscape of power electronic drives, focusing on the evolution of high-efficiency traction motors and next-generation energy storage systems (ESSs), and advancements in ultra-fast chargers. The analysis explores the vital impact of power converters, evaluating recent breakthroughs in wide-bandgap (WBG) semiconductors and advanced control topologies that enhance energy density and thermal management. Furthermore, the study identifies critical challenges in the design, modulation, and operational reliability of converters under dynamic automotive environments. By synthesizing current research trends and technical bottlenecks, this paper offers insights into the future trajectory of power electronics in achieving high-performance, cost-effective, and carbon-neutral transportation. Full article

Although PI and PID controllers are mature control laws, their effect on energy-related variables is rarely isolated in a complete electric vehicle traction model when the plant, controller tuning basis and driving conditions are kept unchanged. A full-system MATLAB/Simulink model was developed, comprising a DC motor with PWM H-bridge, reduction gear, vehicle dynamics and a lithium-ion battery with SOC monitoring. Fixed-gain PI and PID configurations were compared under FTP75, with US06 added as a dynamic-cycle assessment. Speed tracking was evaluated using RMSE, MAE, IAE and ITAE, while energy behavior was assessed through SOC depletion, battery voltage, current and braking-command signals. Under FTP75, both controllers achieved nearly identical tracking accuracy, with an overall RMSE of 0.1525 km/h across the active intervals. Despite this kinematic equivalence, PID reduced SOC depletion by 0.980 percentage points over 4.963 km and produced a less intense but more distributed braking command. The additional 600 s US06 simulation did not confirm a general PID advantage: both controllers reached the same maximum speed and showed practically identical tracking accuracy, while PID did not reduce SOC depletion. The results show that the derivative channel changes the control-command pattern, but it does not automatically improve kinematic or energy performance under fixed-gain tuning. Full article

Traditional optimization methods for interior permanent magnet synchronous motors (IPMSMs) often treat the stator and rotor as independent design domains, which limits the potential for suppressing torque fluctuations due to the neglected electromagnetic coupling between these components. This paper proposes a synergistic optimization strategy for a 120 kW IPMSM, aiming to overcome the inherent limitations of conventional unilateral optimization in design space exploration and achieve global performance enhancement through cross-domain collaboration. By establishing a unified surrogate model incorporating both stator slot geometries and rotor pole topologies, the collaborative effect of seven high-sensitivity design variables is systematically analyzed. The NSGA-II algorithm, coupled with a Kriging surrogate model, is employed to navigate the complex trade-offs among average torque, torque ripple, and cogging torque. Results demonstrate that the synergistic approach achieves a 28.1% reduction in torque ripple while maintaining high average torque, demonstrating superior improvement over conventional stator-only or rotor-only optimization schemes. Analysis based on Maxwell stress tensors and air-gap permeance functions reveals that the proposed method achieves simultaneous suppression of cogging torque and torque ripple by effectively harmonizing the 24th and 48th spatial harmonics. This study provides an efficient synergistic design methodology for the comprehensive performance enhancement of traction motors, offering practical reference value for the engineering development of high-performance electric vehicles. Full article

Pure electric construction machinery (PECM) is gradually becoming the mainstream choice for industrial construction. This paper presents a new configuration of an integrated charger for PECM. The proposed configuration employs a nine-switch-converter (NSC) that can achieve charging and traction functions for the target application. In charging mode, the motor is reused as a filter inductor and the NSC is reused as a conventional three-phase PWM rectifier. Data-driven adaptive predictive control (DAPC) based on recursive least squares (RLS) is proposed to cope with the motor’s saturation problem in charging mode. This control has the advantages of excellent robustness and fast dynamic response. Although the initial parameters are derived from the system model in the first sampling cycle, the controller subsequently relies entirely on online identification, which significantly reduces the sensitivity to parameter accuracy and eliminates the need for manual tuning of controller gains. In propulsion mode, the NSC enables independent operation of the two motors. The proposed configuration improves the utilization of devices and motors, which greatly reduces the weight, volume, and cost of the charger. Finally, an experimental platform was built to verify the feasibility and validity of the proposed topology and control algorithm. Full article

The purpose of this study is to develop a robot that reduces labor and automates cable-laying work at construction sites. The robot should have the ability to pull lead cables over cable racks and ceiling spaces. Therefore, we propose a reconfigured active-cord-mechanism robot based on the RSAW mechanism that can move in both environments by maintaining continuous traveling wave propagation across multiple units connected through joints. A prototype robot was first constructed to verify the applicability of the RSAW mechanism to cable-laying environments. However, the discontinuity of the traveling wave at the joint connections prevented the prototype from traversing ceiling spaces. Based on this finding, a new robot was developed with a configuration that ensures continuous wave propagation across the joints through mechanical design and phase synchronization control. As a result, the new robot enhances propulsion speed and cable traction. Additionally, the robot can move over ceiling joint receivers that exist in ceiling spaces. Comparative analysis with previous prototype robots and a snake-like robot highlights this robot’s advantages, including reduced motor count, autonomous operation with mounted power and control units, and superior turning capabilities. Full article

Electric vehicle (EV) adoption in South Africa remains constrained by high upfront purchase costs, limited charging infrastructure, and policy uncertainty, creating a need for lower-cost and locally relevant pathways to transport decarbonisation. This study evaluates the feasibility of converting a legacy light commercial pickup platform from internal combustion engine (ICE) propulsion to battery-electric propulsion through integrated component sizing, longitudinal vehicle simulation, and techno-economic assessment. A retrofit architecture comprising a traction battery, inverter-controller, electric motor, and DC-DC converter was developed using first-principles vehicle dynamics and energy-demand analysis. The resulting configuration employed a 40 kW AC induction motor, an approximately 28 kWh battery pack, a 40–60 kW inverter with 60 kW peak capability, and a 0.75–1.2 kW auxiliary DC-DC converter. Simulation over a representative 1000 s drive cycle showed stable speed tracking, sustained vehicle motion over approximately 10 km, and peak battery currents exceeding 300 A during acceleration, while regenerative braking reduced net cumulative energy consumption relative to gross demand. The economic analysis indicated that the retrofit pathway yielded the lowest cumulative total cost of ownership over most of a 10-year horizon, with breakeven relative to the used ICE baseline occurring at approximately 3.4 years. Lifecycle analysis further showed that the retrofit configuration achieved the lowest combined production and operational carbon burden among the compared vehicle pathways. These findings indicate that ICE-to-EV retrofitting of legacy light commercial vehicles can provide a technically feasible, economically competitive, and environmentally advantageous electrification strategy for South Africa and comparable emerging markets. Full article

Traditional approaches for identifying bearing defects in metro traction systems often suffer from low diagnostic efficiency and accuracy. To address this, we propose an information fusion approach using the Bat Algorithm-Optimized Variational Mode Decomposition (BA-VMD) and the Self-Attention Convolutional Neural Network (SA-CNN). Vibration and acoustic emission signals are denoised via BA-VMD to optimize decomposition, followed by a diagnosis model utilizing attention-based fusion and SA-CNN to enhance key feature extraction. Experiments on subway traction motor bearings under varying operating conditions demonstrate the method’s efficacy. Results indicate that BA-VMD achieves a signal-to-noise ratio of 6.791, which is 1.595 higher than that of EMD (5.196). Furthermore, the SA-CNN model achieves an average diagnostic accuracy of 98.6%, significantly outperforming MLP (93.57%) and SVM (90.90%). These findings confirm that the proposed framework ensures accurate and stable bearing fault detection in highly variable operating conditions. Full article

The electrification of regional railway lines using battery-electric trains requires accurate simulation tools to support energy management and thermal control design. This paper presents an integrated dynamic simulation model of the traction system of a Hitachi Caravaggio ETR 521 regional train operating in battery-electric mode, developed in MATLAB/Simulink 2024b. The model incorporates all key drivetrain components, including a train reference generator, speed controller, motor controller, three-phase inverter, induction motor, a Kokam Co., Ltd. lithium-ion battery pack, and a detailed battery thermal management system. The proposed framework enables simultaneous evaluation of traction performance, battery state of charge (SOC) evolution, and thermal behavior under realistic conditions. To validate the model, simulations of the Treviso–Vicenza route were conducted under two scenarios: traction-only operation and operation with a 160 kW auxiliary load. Simulation results demonstrate that auxiliary loads significantly affect energy consumption and battery thermal behavior, with energy consumption increased by 50%. The results highlight the importance of integrating thermal effects into energy management and sizing decisions for battery-electric regional trains. The developed model provides a practical tool for optimizing battery sizing, thermal management strategies, and overall energy performance, supporting the planning and design of sustainable electric railway solutions. The modular MATLAB/Simulink architecture is designed to be route-agnostic; extension to other regional lines with different gradients, speed profiles, or extreme climate conditions (e.g., alpine routes or high-temperature regions) requires only updated route data and adjusted ambient boundary conditions, demonstrating the model’s broad applicability beyond the Treviso–Vicenza case study. Full article

The requirement of sustainable mobility and a clean environment has accelerated the development and adoption of electric vehicles (EVs) and hybrid electric vehicles (HEVs) as an alternative, practical and promising solution against conventional vehicles globally. Such alternative energy vehicles not only provide a critical solution to mitigate fossil fuel dependency and reduce greenhouse gas emissions, but also contribute to producing an energy-efficient transportation system. However, the operational performance, efficiency, and cost-effectiveness of EVs and HEVs are hugely dependent on their powertrain architectures, selection of traction motors and associated control techniques. This paper systematically compares major hybrid architectures: series, parallel, and series–parallel, plug-in, as well as battery and fuel cell electric vehicle platforms, highlighting trade-offs in component sizing, cost, and system integration complexity. The paper critically analyses traction motor technologies with respect to torque–speed characteristics, efficiency behavior, material constraints, and power density. A detailed comparative assessment of traction motor technologies is presented. Furthermore, classical and advanced motor control strategies, including field-oriented control (FOC), direct torque control (DTC), model predictive control (MPC) and AI-enhanced control frameworks, are evaluated with respect to transient performance, robustness, computational requirements, and scalability. The review identifies key technological milestones, emerging next-generation drive technologies, existing limitations, and unresolved research challenges. Finally, critical research gaps and future development pathways are articulated to support the advancement of high-efficiency, reliable, and cost-effective EV/HEV powertrain systems. Full article

Aiming at solving the problems of severe chattering, irreconcilable convergence speed, and steady-state accuracy in traditional sliding-mode control (SMC) for the speed regulation system of permanent magnet synchronous motors (PMSMs) in rail transit traction, as well as its poor adaptability to complex disturbances such as frequent acceleration/deceleration and sudden load changes under traction conditions, a sliding-mode control strategy integrating improved piecewise terminal integral sliding-mode control (IPTISMC) with an adaptive smooth exponential reaching law (ASERL) is proposed. Taking the surface-mounted PMSM for rail transit traction as the research object, the d-q axis mathematical model is established, and a terminal integral sliding surface with a piecewise nonlinear function is designed, which resolves the problems of complex solutions and steady-state errors of the traditional sliding surface through a piecewise cooperative mechanism for large and small error stages. The designed ASERL realizes adaptive gain adjustment based on the state variables of the sliding surface and replaces the sign function with the hyperbolic tangent function, thus alleviating the inherent contradiction between convergence and chattering in the fixed-gain reaching law. The global stability and finite-time convergence of the system are rigorously proved based on Lyapunov stability theory. Furthermore, comparative experiments involving no-load operation, acceleration and deceleration, sudden load application and removal, and parameter perturbation are carried out on a DSP experimental platform for SMC-ERL, ISMC-ERL, IPTISMC-ERL and the proposed IPTISMC-ASERL. Experimental results show that the proposed IPTISMC-ASERL strategy can significantly improve the dynamic response and steady-state control accuracy of the PMSM speed regulation system for rail transit traction, effectively suppress chattering to enhance riding comfort, and simultaneously strengthen the system’s anti-disturbance capability and parametric robustness. It can fully meet the engineering control requirements for high precision and high stability of PMSMs in rail transit traction applications. Full article

The electrification of urban and industrial transport is driving the need for propulsion architectures that combine energy efficiency, operational flexibility and regulatory compliance. However, current electric platforms often lack the adaptability required for customized body configurations and multistage manufacturing, and their approval is hindered by the complexity of meeting electrical safety and electromagnetic compatibility (EMC) requirements at vehicle level. This article presents the conceptual design of a modular electric propulsion module developed within the MODULe project, in which the traction motor, inverter, battery pack, Battery Management System (BMS) and cooling circuits are integrated into a standardized module conceived as an Independent Technical Unit (ITU). The propulsion module dimensioned using a modified WLTP cycle, and the results indicate that the selected components can meet the dynamic demands of light and medium-duty vehicles, achieving an estimated consumption of around 50 kWh/100 km and a driving range above 160 km. By concentrating the critical regulatory requirements within a single module, the proposed architecture facilitates multistage vehicle approval, reduces development effort and supports the scalable electrification of commercial fleets. This approach may contribute to accelerating the deployment of zero-emission vehicles in urban logistics and industrial applications, with potential benefits for both the sector and society. Full article

High-speed operation is a key pathway to higher power density in modern EV traction systems, and multi-parameter optimization is essential for enhancing its high-speed performance. This study investigates a 20,000 r/min interior double-V permanent-magnet flat-wire motor via finite-element simulations to systematically examine the effects of multiple interacting parameters—including flat-wire layer number, stator slot geometry, magnet grade, and rotor magnetic barrier angle—on the electromagnetic performance under high-speed operating conditions. The results indicate that increasing winding layers significantly reduces high-speed torque; an eight-layer design decreases torque by about 50% compared to a four-layer one, while a six-layer arrangement offers a favorable torque-loss trade-off. Wider slots lower the average torque but reduce torque ripple by approximately 27%, whereas deeper slots increase tooth flux density and reduce efficiency. Higher-grade magnets enhance air-gap flux and torque at elevated cost. Rotor magnet angle optimization reveals a trade-off between peak torque and ripple, with a symmetric 100°/100° design achieving balanced performance. These findings clarify structural–control interactions and support the multi-objective design of high-speed flat-wire permanent-magnet motors. Full article

Axial Flux Permanent Magnet Synchronous Motors (AFPMSMs) are gaining increasing attention for their application in electric vehicle (EV) drive systems. Their high torque density and compact axial geometry make them attractive for high-performance EV drive systems. However, cogging torque remains a major challenge, degrading low-speed drivability, noise performance, and control stability. This article proposes a magnet skew on rotor modulation structure using a genetic algorithm (GA) to reduce cogging torque in AFPMSMs utilizing a 12/15 non-integer pole/slot arrangement. The objective of optimization is to simultaneously reduce cogging torque under identical electromagnetic constraints. A complete three-dimensional finite element model (3D-FEM) incorporating nonlinear magnetic material properties has been developed to evaluate the electromagnetic field distribution and torque components. The results indicate that a 12/15 non-integer pole/slot arrangement improves harmonic distribution and extends the operating range with lower cogging torque compared to integer pole/slot designs. Combined with GA-optimized skew angles, this reduces peak-to-peak cogging torque to less than 50%. This design is ideally suited for the traction requirements of electric vehicles, including premium electric vehicles where smooth operation at low speeds is critical. Full article

This research paper presents Volvo SmartCell, an AC battery technology that integrates modular multilevel converters and battery cells to form a unified system for electric vehicle propulsion and power supply. The research work addresses the broader challenge of reducing driveline cost and complexity by replacing traditional components such as inverters, onboard chargers, centralized DC/DC converters, vehicle control units and many more. SmartCell uses distributed Cluster Boards comprised of H-bridges which are controlled via wireless communication to generate AC voltage, deliver redundant low voltage power, and support cell level protection mechanisms. The prototype testing demonstrates that the system can supply traction power by engaging clusters according to the required voltage depending on motor speed, achieve AC grid charging by synthesizing sinusoidal voltages without a dedicated charger, and provide autonomous DC/DC operation through cluster level voltage regulation. Simulations further indicate that multilevel voltage generation can reduce switching losses and improve electric machine efficiency compared to conventional systems. Additional benefits include active cell balancing, support for mixed cell chemistries, and high redundancy through multiple independent power branches. Challenges remain in wireless bandwidth limitations and cost optimization of Cluster Boards. Ongoing development aims to enhance communication robustness and validate safety for non-isolated grid charging. Full article