Aiming at the problem of trajectory tracking and handling stability of intelligent four hub-motor independent-drive electric vehicle at high speed, an integrated control strategy based on model predictive control (MPC) is proposed. Firstly, a kinematics preview model is established considering the adaptive change of preview distance with longitudinal vehicle speed. Secondly, combined with the proposed preview model and considering the vehicle dynamic characteristics, an upper level controller of MPC is created to track the lateral deviation, heading angle deviation, sideslip angle and yaw rate to obtain the optimal solution of front wheel angle and additional yaw moment, which realize the control of handling stability while ensuring the trajectory tracking accuracy at same time. Then considering the varying road adhesion and the influence of longitudinal slip at the four tires, a lower level controller composed of torque optimal control and sliding mode controller is designed to realize the optimal torque distribution of four hub motors. Finally, through the co-simulation of MATLAB / Simulink and CarSim and the hardware-in-the-loop experiment, it is verified that the proposed integrated control strategy can effectively improve the path tracking accuracy and ensure the vehicle handling stability at high speed. Compared with the general MPC strategy, who does not control the sideslip angle and yaw rate with no preview model, the cumulative lateral tracking error of the integrated control is reduced by 51.9% and 87.7% respectively.

In this paper, a continuous steering stability controller based on an energy-saving torque distribution algorithm is proposed for a four in-wheel-motor independent-drive electric vehicle (4MIDEV) to improve the energy consumption efficiency while maintaining the stability in steering maneuvers. The controller is designed as a hierarchical structure, including the reference model level, the upper-level controller, and the lower-level controller. The upper-level controller adopts the direct yaw moment control (DYC), which is designed to work continuously during the steering maneuver to better ensure steering stability in extreme situations, rather than working only after the vehicle is judged to be unstable. An adaptive two-hierarchy energy-saving torque distribution algorithm is developed in the lower-level controller with the friction ellipse constraint as a basis for judging whether the algorithm needs to be switched, so as to achieve a more stable and energy-efficient steering operation. The proposed stability controller was validated in a co-simulation of CarSim and Matlab/Simulink. The simulation results under different steering maneuvers indicate that the proposed controller, compared with the conventional servo controller and the ordinary continuous controller, can reduce energy consumption up to 23.68% and improve the vehicle steering stability.

This article presents a post-impact lateral stability control strategy integrated for Four Hub-Motor Independent-Drive Electric Vehicles (4MIDEV) to address the issue of loss of vehicle stability control due to vehicle skidding and saturated tire forces upon light vehicle collision using active front steering (AFS) and direct yaw moment control (DYC). Upon a light vehicle collision, vehicle experiences lateral and yaw motions due to collision impact-induced yaw moment. A multiple-objective hierarchical control strategy to attenuate vehicle yaw moment and regain stability control is proposed. Two potential sets of control reference states for the control strategy motion control are considered: desired DYC states and the drift equilibrium. A direct yaw moment controller based on sliding mode control (SMC) theory is designed to track the desired yaw rate. For the AFS, the tracking of desired DYC sideslip angle is performed using a SMC based controller, whereas the tracking of drift equilibrium state values employs a state feedback controller. An SMC longitudinal controller is designed for deceleration control of the vehicle after collision. Upon compensation of the yaw moment, a multiple sliding surface control theory-based lane controller is employed for lateral path deviation and heading angle control. The effectiveness of the proposed control strategy is validated on Carsim and Matlab/Simulink joint simulation platform. Simulation results showed that the proposed control strategy is effective in improving the post-impact stability control of the 4MIDEV on a high-velocity condition, and the control strategy that tracks the drift equilibrium showed better control performance on low adhesion coefficient surface.

A trajectory planning method for local obstacle avoidance based on an improved artificial potential field (APF) method is proposed, which is aimed at the problem for dual motor driven unmanned tracked vehicles avoiding dynamic and static obstacles in unstructured environments. Firstly, in traditional artificial potential fields, by adding virtual target points, unmanned tracked vehicles can avoid large obstacles and reach the target point in off-road environments. Secondly, a water droplet type repulsive potential field function for static obstacles and an improved dynamic obstacle potential field function including relative velocity function and relative acceleration function are established in the proposed improved APF method to improve the smoothness of lane changing obstacle avoidance paths. The simulation results of overtaking and obstacle avoidance in the same direction show that the change in heading angle is reduced by 42.9%, and the lateral displacement is reduced by 39.5%. Finally, a trajectory planning method based on improved APF for obstacle avoidance and lane changing of the unmanned tracked vehicle is constructed, which also considers the speed planning with kinematic and dynamic constraints. For obstacle avoidance under lateral meeting condition, the collaborative simulation results of Prescan-Adams-Matlab/Simulink show that the change in heading angle is reduced by 84%, and the lateral displacement is almost zero. Under complex working conditions with multiple static and dynamic obstacles, the results of hardware in loop (HIL) simulation testing and vehicle experiments show that the number of drastic changes in turning radius and heading angle of the vehicle is significantly reduced, and the maximum amplitude was reduced by 63.2% and 37.5% respectively, making the vehicle’s obstacle avoidance and lane changing safer, smoother, and more efficient.

The large dv/dt and di/dt outputs of power devices in DC-fed motor drive systems in electric vehicles (EVs) always introduce conducted electromagnetic interference (EMI) emissions and may lead to motor drive system energy transmission losses. The effect of distributed parameters on conducted EMI from the DC-fed high voltage motor drive systems in EVs is studied. A complete test for conducted EMI from the direct current fed(DC-fed) alternating current (AC) motor drive system in an electric vehicle (EV) under load conditions is set up to measure the conducted EMI of high voltage DC cables and the EMI noise peaks due to resonances in a frequency range of 150 kHz–108 MHz. The distributed parameters of the motor can induce bearing currents under low frequency sine wave operation. However the impedance of the distributed parameters of the motor is very high at resonance frequencies of 500 kHz and 30 MHz, and the effect of the bearing current can be ignored, so the research mainly focuses on the distributed parameters in inverters and cables at 500 kHz and 30 MHz, not the effect of distributed parameters of the motor on resonances. The corresponding equivalent circuits for differential mode (DM) and common mode (CM) EMI at resonance frequencies of 500 kHz and 30 MHz are established to determine the EMI propagation paths and analyze the effect of distributed parameters on conducted EMI. The dominant distributed parameters of elements responsible for the appearing resonances at 500 kHz and 30 MHz are determined. The effect of the dominant distributed parameters on conducted EMI are presented and verified by simulation and experiment. The conduced voltage at frequencies from 150 kHz to 108 MHz can be mitigated to below the limit level-3 of CISPR25 by changing the dominant distributed parameters.

Automatic lane detection for driver assistance is a significant component in developing advanced driver assistance systems and high-level application frameworks since it contributes to driver and pedestrian safety on roads and highways. However, due to several limitations that lane detection systems must rectify, such as the uncertainties of lane patterns, perspective consequences, limited visibility of lane lines, dark spots, complex background, illuminance, and light reflections, it remains a challenging task. The proposed method employs vision-based technologies to determine the lane boundary lines. We devised a system for correctly identifying lane lines on a homogeneous road surface. Lane line detection relies heavily on the gradient and hue lightness saturation (HLS) thresholding which detects the lane line in binary images. The lanes are shown, and a sliding window searching method is used to estimate the color lane. The proposed system achieved 96% accuracy in detecting lane lines on the different roads, and its performance was assessed using data from several road image databases under various illumination circumstances.