Recently, there has been significant attention given to the electrification of transportation due to concerns about fossil fuel depletion and environmental pollution. Conventional drive systems typically include a clutch, reduction gear, and mechanical differential, which results in power loss, noise, vibration, and additional maintenance. However, in-wheel motor drive technology eliminates the need for these components, providing benefits such as higher system efficiency, improved wheel control, and increased passenger comfort. This article offers a comprehensive review of the technology and development of in-wheel motor drives. It begins with an overview of in-wheel motor drives in electric vehicles, followed by an exploration of the types of electric motors suitable for in-wheel motor drives. The paper then presents an industrial state of the art of in-wheel motors, comparing them with conventional motor drives, and reviews the implemented power electronics, control system, and cooling systems. Finally, the paper concludes by providing an outlook on the challenges and future trends of in-wheel drive systems.

/pdf/in-wheel-motor-drive-systems-for-electric-vehicles-state-of-3soz6wiu.pdf

In-Wheel Motor Drive Systems for Electric Vehicles: State of the Art, Challenges, and Future Trends

The enhancement of vehicle passenger safety is a central theme for car manufacturers. Since the introduction of Electronic Stability Control (ESC) in the late 90s, researchers in industry and academia have kept striving for continuously enhancing vehicle safety. However, despite significant efforts, the literature shows that a significant number of these endeavors have not advanced beyond theoretical formulations and software simulations. This article presents the testing journey of an individual-wheel-torque-based vehicle stability controller through the major milestones of its development cycle. First, the controller is formulated based on specific vehicle dynamics design requirements. Then, an offline co-simulation is put in place to validate the controller along relevant maneuvers, with the controller running on Matlab-Simulink concurrently with the software Amesim running a 15-dof vehicle model of Siemens' SimRod battery electric vehicle. Next, a real-time co-simulation is achieved, running both the controller and the vehicle model on a real-time platform. Finally, an experimental hardware-in-the-loop setup is built, incorporating a dedicated Electronic Control Unit (ECU), and successfully tested.

Hardware-in-the-loop Real-time Implementation of a Vehicle Stability Control Through Individual Wheel Torques

Speed inconsistency in multi-motor systems may lead to mechanical structure damage, low cooperative precision, and even cause equipment breakdown. Traditional control methods may induce pronounced consensus error fluctuations and prolonged convergence time under complex conditions such as system parameter mismatch, sudden load changes, and inaccurate mechanism models. To address these challenges, we propose a fixed-time cooperative model-free sliding mode control (FCM-SMC) method based on a fractional-order ultra-local model (FOULM). Specifically, the proposed approach integrates fractional-order dynamics into the system model to better capture the non-integer order characteristics of multi-motor systems. Then, to estimate the unknown terms of FOULM, a novel fixed-time disturbance observer (FTDO) is designed. Additionally, grounded in the framework of FOULM, the FCM-SMC protocol is designed to ensure that the consensus error of the multi-motor systems converges within a fixed time. Taking motor #1 as an example, compared with existing methods, the error metrics (ME, MAE, and RMSE) of the proposed method are reduced by up to 64.8%, 70.2%, and 69.7%, respectively. Note to Practitioners—This paper was motivated by the problem of speed consensus for multi-motors. This problem presents certain challenges in relevant industrial applications, such as urban rail trains and electric vehicles. In this research, the dynamics of the multi-motor system are formulated in accordance with the fractional-order theory and model-free theory. Subsequently, we demonstrate how to design the FTDO and the FCM-SMC protocol according to the state equations, so that the speed consensus error of the multi-motor system can converge within a fixed-time upper bound. However, it is unable to precisely provide the specific convergence moment. Ultimately, the experimental results validate the practical effectiveness of the proposed approach. The proposed FCM-SMC protocol exhibits the potential for broader applicability and can be effectively extrapolated to diverse categories of multi-motor systems. In the subsequent research, we will further explore the application of the predefined-time algorithm in multi-motor systems under the consideration of time-varying topologies on this basis.

Fixed-Time Cooperative Model-Free Sliding Mode Control for Fractional-Order Multi-Motor Systems

Guest Editorial Introduction to the Special Section on Next Generation Zero-Emission Vehicles

Improving vehicle passenger safety is of major importance in modern automotive industry. Within this framework, vehicle stability controllers play a key role, as they actively contribute to maintain vehicle driveability even in potentially dangerous situations. An example of such a controller is Electronic Stability Control (ESC), that brakes individual wheels to generate a direct yaw moment to stabilize the vehicle (e.g. from excessive understeer or oversteer). This paper presents the real-time implementation of a stability controller based on measured (and/or estimated) yaw rate and sideslip angle and on phase-plane related stability criteria. The control strategy is first developed in MATLAB-Simulink environment with a simplified vehicle model. Then, the controller is assessed via software-in-the-loop using a full vehicle model developed in Simcenter Amesim, before implementing it on a real-time platform. Results are promising, endorsing the implementation of hardware-in-the-loop using an Electronic Control Unit.

Real-time implementation of yaw rate and sideslip control through individual wheel torques

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Real-time implementation of yaw rate and sideslip control through individual wheel torques

Hardware-in-the-loop Real-time Implementation of a Vehicle Stability Control Through Individual Wheel Torques