In this paper, a longitudinal control strategy in terms of model predictive control (MPC) and mass estimator is investigated for an autonomous electric vehicle (AEV). A driving force table (DFT) is established to represent the relationship among throttle opening, speed, and driving force. A mass estimator is designed to obtain the actual mass of AEV. An MPC-based controller with constraints is suggested to get the desired acceleration. Moreover, a feedforward controller is developed to calculate the throttle opening directly. Both the iterative feasibility and stability of the MPC are ensured. The experimental results are given to show the effectiveness of our strategy with mass estimator. KEYWORDSlongitudinal control, model predictive control (MPC), mass estimator, driving force table (DFT), autonomous electric vehicle (AEV)

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