A Novel Anti-Saturation Model-Free Adaptive Control Algorithm and Its Application in the Electric Vehicle Braking Energy Recovery System

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In this work, a novel anti-saturation model-free adaptive control (AS-MFAC) algorithm is proposed for the problem of pure electric vehicle’s braking energy recovery with the uncertain dynamic external factors. In the process of energy recovery during vehicle braking, actuator saturation and error accumulation occur due to various external conditions. In AS-MFAC, the non-linear dynamics of the vehicle braking energy recovery process is firstly linearized via a novel dynamical linearization technique with a time-varying parameter pseudo partial derivative (PPD). Then, by proposing the concept of the saturation parameter, the AS-MFAC controller is designed. Consequently, the stability and safety of the braking system are guaranteed while ensuring energy recovery. The major advantages of the AS-MFAC algorithm are that the controller uses only input and output data from the regenerative braking control system and this approach addresses the actuator saturation problem as well as provides a feasible solution. Moreover, the stability of the AS-MFAC algorithm is proven by rigorous mathematical theory and its effectiveness is verified by a series of experimental simulations. Remarkably, the proposed AS-MFAC controller has the property of symmetry since the controller structure and the corresponding parameter (time-varying PPD) estimator are both inferred based on the project algorithm. Consequently, the structures of the controller and the parameters of AS-MFAC have a symmetric similarity.