Adaptive Car-Following Control of Intelligent Electric Vehicles

This article proposes an adaptive fuzzy sliding mode control method for longitudinal motion of intelligent electric vehicles (IEVs) with nonlinear and strong time-varying characteristics under uncertainty interference. A dynamic system model is established to characterize the mechanism of IEVs longitudinal behavior. An adaptive hierarchical control architecture is constructed in which the upper control layer is for obtaining sliding mode control law of the desired acceleration based on the inter-vehicle state information. A fuzzy system is utilized to optimize the sliding mode control to realize adaptive control, which can effectively overcome the parameter uncertainty characteristics of IEVs. In the lower control layer, a switch logic with hysteresis boundary is developed to ensure ride comfort, and the expected torque is calculated in real time based on the inverse dynamic model to track the desired acceleration planned by the upper control layer. Simulations results show that the proposed adaptive control method has great potential to guarantee the tracking capability and security at the same time provide a robustness to the interference of the preceding vehicle acceleration during car-following process.