Abstract
Regenerative braking is the key to achieve efficient use of energy and extend the driving range in pure electric vehicles. This study proposes a new predictive control method integrating adaptive cubic exponential prediction and dynamic programming to address the problem of efficient energy recovery during the regular braking process of four-wheel pure electric vehicles. The method considers the dynamic characteristics of an electro-hydraulic combined braking system. The adaptive cubic exponential prediction is adopted to predict the vehicle velocity and braking intensity. The dynamic programming is employed to optimize the motor braking torques and wheel cylinder pressures under the condition of braking regulations, road constraints, and vehicle constraints. To verify the effectiveness of the new predictive control method, the ideal and multi-stage braking force distribution methods are employed for comparison. The results confirm that, under gradual braking conditions, the energy recovery efficiency achieved via the proposed method is improved by 1.55% and 6.40% considering the ideal and multi-stage braking force distribution methods, respectively.
Highlights
As the development of zero-emission pure electric vehicles is beneficial to the global environment [1]–[3], they are being increasingly developed and deployed worldwide [4].Some researchers have conducted in-depth studies on electric vehicles, including handling stability control [5], yaw stability control [6], and inertial estimation [7]
Research indicates that 50% of the energy of pure electric vehicles is wasted in the form of heat by a conventional braking system during deceleration in urban conditions [8]
To solve the mentioned issues, a predictive control method (PCM) that centers on the future of vehicle state information and dynamic characteristics of the electro-hydraulic combined braking system is proposed for four-wheel pure electric vehicles to improve energy recovery efficiency
Summary
As the development of zero-emission pure electric vehicles is beneficial to the global environment [1]–[3], they are being increasingly developed and deployed worldwide [4]. Regarding rule-based control, early research mainly considered the regulations of the Economic Commission for Europe (ECE) and ideal braking force distribution [24] This can improve the energy recovery efficiency, it does not consider the driver’s intention recognition. Fuzzy logic optimized by genetic algorithm [28] was adopted to obtain electro-hydraulic braking force distribution rules This method did not consider the driver’s intention recognition, other studies considered this aspect [29] [30], obtaining an improvement in energy recovery efficiency, the dynamic characteristics of the system were neglected, as well as the future state information of the vehicle. To solve the mentioned issues, a predictive control method (PCM) that centers on the future of vehicle state information and dynamic characteristics of the electro-hydraulic combined braking system is proposed for four-wheel pure electric vehicles to improve energy recovery efficiency. The motors, main reducers, and wheels are mechanically connected, and the wheel cylinders and the braking unit are connected by pipelines
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