基于输入输出约束的无模型自适应控制算法的电动汽车制动能量回收新方法

Shida Liu, Zhen Li, Honghai Ji, Z. Hou, Lingling Fan
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引用次数: 2

摘要

本文主要研究动态外部因素不确定的纯电动汽车制动能量回收问题。针对这一问题,提出了一种新的无模型输入输出约束自适应控制方法(IOC-MFAC)。动态过程可以看作是以液压制动转矩和电机制动转矩为输入,制动能量和制动减速度为输出的非线性二输入二输出系统。利用oc - mfac,考虑了电流和电压限制对电机最大制动转矩的约束以及车辆舒适性对制动减速的约束。从而在保证能量回收的同时,将回收能量控制在一个稳定的范围内,延长蓄电池的使用寿命。oc - mfac的主要优点是不仅控制器设计时只考虑再生制动控制系统的输入和输出数据,而且考虑了系统输入和输出的约束条件。此外,通过一系列数值模拟验证了IOC-MFAC的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel Electric Vehicle Braking Energy Recovery Method Based on Model Free Adaptive Control Algorithm with Input and Output Constraints
This study focus on the problem of pure electric vehicle's braking energy recovery with the uncertain dynamic external factors. For this problem, a novel model free adaptive control with input and output constraints (IOC-MFAC) method is introduced. The dynamic process can be considered as a nonlinear two inputs and two outputs system with hydraulic braking torque and motor braking torque as inputs and braking energy and braking deceleration as outputs. By using IOC-MFAC, the constraints of limitation of current and voltage on the maximum motor braking torque and the constraints of the vehicle's comfort on braking deceleration are considered. Consequently, the recovered energy is controlled in a stable range while guaranteeing the energy recovery to prolong the storage battery's operating life. The major advantages of IOC-MFAC are that not only the controller is designed only with input and output data of the regenerative brake control system, but also the constraints of the system inputs and outputs are considered. Further, the efficiency of IOC-MFAC is verified with a series of numerical simulations.
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