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Regenerative Braking Control Method Based on Predictive Optimization for Four-Wheel Drive Pure Electric Vehicle

机译:基于四轮驱动纯电动车预测优化的再生制动控制方法

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摘要

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.
机译:再生制动是实现能量有效利用的关键,并在纯电动车辆中延伸驾驶范围。本研究提出了一种新的预测控制方法,其集成了自适应立方指数预测和动态规划,以解决四轮纯电动车辆的常规制动过程中有效的能量回收问题。该方法考虑了电液组合制动系统的动态特性。采用自适应立方指数预测来预测车辆速度和制动强度。采用动态规划,以优化在制动规范,道路限制和车辆约束的条件下的电动机制动扭矩和轮缸压力。为了验证新的预测控制方法的有效性,采用理想和多级制动力分布方法进行比较。结果证实,在逐步制动条件下,考虑到理想和多级制动力分布方法,通过所提出的方法实现的能量回收效率得到了1.55%和6.40%。

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