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Significant nonlinearity of electronic hydraulic brake (EHB) systems often leads to complex hydraulic force control responses. This paper designs a motor-driven EHB system and analyzes nonlinear friction induced by the deceleration mechanism. To compensate this friction, a flutter signal is added to the controller input. In addition, this paper designs a fuzzy-PI (Proportional and Integral) controller for the cylinder hydraulic pressure of the EHB system based on the opening and closing characteristics of a solenoid valve. Response curves of cylinder hydraulic pressure are obtained under three different input signals: step, triangular, and sinusoidal. The co-simulation model is established by AMEsim TM and Simulink R ansofts. The study results indicate that the proposed hydraulic-forcefollowing control method of the EHB system can follow different input signals well. A step response test and a sine-wave-following test are carried out, which correspond to the EHB response in the case of driver's emergency braking and frequent braking, respectively. Stable and rapid pressure build-up is obtained under different step target hydraulic pressures. Therefore, the hydraulic-force-following control method of the EHB system based on a fuzzy-PI controller can satisfy the EHB system accuracy requirements for an electric vehicle, which is a certain valuable for the automobile industry.

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Regenerative braking is a key technology for electric vehicles to improve energy efficiency and extend driving range. Considering the impact of road surface adhesion coefficient in the regenerative braking process of vehicles is a meaningful but challenging problem. To effectively utilize the pavement adhesion coefficient and improve the brake energy recovery effect, a pavement observer‐based regenerative braking control strategy for pure electric vehicles is proposed. The control strategy can identify the pavement based on correction factor by analogy idea according to the real‐time state information of vehicles. The optimal braking force distribution coefficient under different pavements is obtained by Fmincon function based on interior point algorithm. The effectiveness of the control strategy is verified by Simulink/CarSim software cosimulation and road test. The results show that the braking time of the proposed regenerative braking control strategy is reduced by 8.2% and the average actual feedback braking torque is increased by 17.6% in dry asphalt conditions compared with the fixed proportional distribution control strategy. Under the premise of effectively ensuring the braking stability and safety of the vehicle, more energy generated during braking can be recovered.