人工神经网络

2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT) Pub Date : 2019-09-01 DOI:10.1109/ICICT46931.2019.8977685

N. Kumari, V. Bhargava

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引用次数: 0

摘要

本文在MATLAB Simulink中研究并实现了针对电动汽车混合动力储能系统的合理思考问题和不夸张决策的能力。正式提出了一种由锂离子电池和超级电容器组成的混合动力储能系统，为电动汽车充电的方案。采用人工神经网络设计控制系统，对PI控制技术的控制效果进行了改进。通过减少Kp和Ki的计算值，降低了系统的计算复杂度。神经网络提高了系统的自学习能力，并通过减少任何波动来改善系统。本文研究并实现了电动汽车混合储能系统的设计技术。

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Artificial Neural Network

This is studied and implemented in MATLAB Simulink on the ability of think about problems and decisions in a reasonable way without exaggerating of electric vehicles specifically for hybrid energy storage system. It formally suggest something as a possible to plan for hybrid electric storage system consists of lithium ion battery and super capacitor to charge the electric vehicle. The control system is designed using Artificial Neural Network to improve something the results obtained using the PI controlled techniques. It reduces the calculation complexity of the system by reducing the values of Kp and Ki calculations. The neural network promotes self-learning capability of the system and also improves the system by reducing any fluctuations if any. In this paper, we study and implement techniques for design of Hybrid Energy Storage System for Electric Vehicles.

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来源期刊

2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)

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