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A Novel Electric Vehicle Braking Energy Recovery Method Based on Model Free Adaptive Control Algorithm with Input and Output Constraints

机译:一种新型电动汽车制动能量回收方法,基于模型自适应控制算法输入和输出约束

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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.
机译:本研究侧重于纯电动汽车制动能源回收与不确定的动态外部因素的问题。对于此问题,引入了一种新颖的自由自适应控制,具有输入和输出约束(IOC-MFAC)方法。动态过程可以被认为是非线性两个输入和两个输出系统,其具有液压制动扭矩和电动机制动扭矩作为输入和制动能量和制动减速作为输出。通过使用IOC-MFAC,考虑了最大电动机制动扭矩上的电流和电压的限制和车辆对制动减速时的舒适度的限制。因此,回收的能量在稳定的范围内控制,同时保证能量回收以延长储存电池的使用寿命。 IOC-MFAC的主要优点是,不仅控制器仅使用再生制动控制系统的输入和输出数据设计,而且考虑了系统输入和输出的约束。此外,通过一系列数值模拟验证了IOC-MFAC的效率。

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