Design of a DC/DC Converter with a PID Controller and Backpropagation Neural Network for Electric Vehicles

A. Hussein, Basmah Shigdar, Lina Almatrafi, Batool Alaidroos, F. Alsharif, Rabab Hamed M. Aly
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Abstract

Currently, global warming has become a major problem. The pollution caused because of conventional internal combustion engines are increasing dramatically. Electric Vehicles are good alternatives to conventional IC engine vehicles in promoting a green environment. Controllers, converters, and modulation schemes are needed to provide a safe and reliable power transmission from energy storage systems to the electric motor in electric cars. In this paper, a design of DC/DC boost converter based on a PID controller is proposed. Moreover, a Back Propagation Neural Network (BPNN) technique is applied to generate the optimal PID parameters before using the PID. The proposed DC/DC boost converter is simulated using MATLAB software. The simulation results proved that the proposed DC/DC converter with PID-BPNN achieved higher performance and a stable output voltage.
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基于PID控制器和反向传播神经网络的电动汽车DC/DC变换器设计
目前,全球变暖已成为一个重大问题。传统内燃机造成的污染正在急剧增加。在促进绿色环境方面,电动汽车是传统内燃机汽车的良好替代品。需要控制器、转换器和调制方案来提供从储能系统到电动汽车电动机的安全可靠的电力传输。本文提出了一种基于PID控制器的DC/DC升压变换器的设计方法。此外,在使用PID之前,应用反向传播神经网络(BPNN)技术生成最优PID参数。利用MATLAB软件对所设计的DC/DC升压变换器进行了仿真。仿真结果表明,基于pid - bp神经网络的DC/DC变换器具有较高的性能和稳定的输出电压。
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