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Aiming at the characteristics of time-varying, time-delay and non-linearity of electric vehicle heat pump air-conditioning system, this paper presents a sliding mode control method based on RBF neural network. The RBF neural network can approximate the nonlinear function with arbitrary precision under certain conditions, and has strong self-learning and self-adaptive ability. Combining the RBF neural network with the sliding mode variable structure control not only has the anti-interference of the sliding mode control and the robustness to the parameter changes, but also effectively reduces the flutter caused by the sliding mode control. The simulation results show that the RBF neural network sliding mode control method can improve the system control accuracy, effectively weaken the chattering, and has good adaptability to the interference conditions.

Application of RBF Sliding Mode Control in Pump System for Electric Vehicle Heat Air Conditioning