Abstract: Vehicle active safety control is attracting ever increasing attention in the attempt to improve the stability and the maneuverability of electric vehicles. In this paper, a neural network combined inverse (NNCI) controller is proposed, incorporating the merits of left-inversion and right-inversion. As the left-inversion soft-sensor can estimate the sideslip angle, while the right-inversion is utilized to decouple control. Then, the proposed NNCI controller not only linearizes and decouples the original nonlinear system, but also directly obtains immeasurable state feedback in constructing the right-inversion. Hence, the proposed controller is very practical in engineering applications. The proposed system is co-simulated based on the vehicle simulation package CarSim in connection with Matlab/Simulink. The results verify the effectiveness of the proposed control strategy.
Keywords: neural network combined inverse; soft-sensor; decoupling control; electric vehicles; two-rear-wheel independently driven
Export to BibTeX
MDPI and ACS Style
Zhang, D.; Liu, G.; Zhao, W.; Miao, P.; Jiang, Y.; Zhou, H. A Neural Network Combined Inverse Controller for a Two-Rear-Wheel Independently Driven Electric Vehicle. Energies 2014, 7, 4614-4628.
Zhang D, Liu G, Zhao W, Miao P, Jiang Y, Zhou H. A Neural Network Combined Inverse Controller for a Two-Rear-Wheel Independently Driven Electric Vehicle. Energies. 2014; 7(7):4614-4628.
Zhang, Duo; Liu, Guohai; Zhao, Wenxiang; Miao, Penghu; Jiang, Yan; Zhou, Huawei. 2014. "A Neural Network Combined Inverse Controller for a Two-Rear-Wheel Independently Driven Electric Vehicle." Energies 7, no. 7: 4614-4628.