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A novel driver-assist stability system for all-wheel-drive Electric Vehicles is introduced. The system helps drivers maintain control in the event of a driving emergency, including heavy braking or obstacle avoidance. The system comprises a Fuzzy logic that independently controls wheel torques to prevent vehicle spin. A neural network is trained to generate the required yaw rate reference. Another Fuzzy system for each wheel controls the slip to ensure vehicle stability and safety. Furthermore a new vehicle speed estimator is employed for slip estimation. The intrinsic robustness of fuzzy controllers allows the system to operate in different road conditions successfully. Moreover, the ease to implement fuzzy controllers gives a potential for vehicle stability enhancement.

This paper presents a novel method for motion control and driver stability assist system of an electric vehicle with independently driven wheels. A combination of two controllers for yaw rate and wheel slip is used to improve yaw stability of a two-wheel-drive electric vehicle. Vehicle speed is estimated using a multi-sensor data fusion method. To overcome the uncertainties in tire-road friction, a Fuzzy logic approach is employed for both controllers. The effectiveness of the proposed control method is evaluated by simulation.

The stability of a four motor-wheel drive electric vehicle is improved by independent control of wheel torques. An innovative Fuzzy Direct Yaw Control method together with a novel wheel slip controller is used to enhance the vehicle stability and safety. Also a new speed estimator is presented in this paper, which is used for slip estimation. The intrinsic robustness of fuzzy controllers allows the system to operate in different road conditions successfully. Moreover, the ease to implement fuzzy controllers gives a practical solution for vehicle stability enhancement.