Thermal management with fast temperature convergence based on optimized fuzzy PID algorithm for electric vehicle battery

Liu, Zhangmiaoge; Liu, Zhouxiao; Liu, Jianzhao; Wang, Ning

doi:10.1016/j.apenergy.2023.121936

Cited by 17 publications

(1 citation statement)

References 29 publications

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“…The proportional, integral, and differential coefficients of PID controllers need to be tuned before control [11]. For some scenarios where the coefficients need to be adjusted in real time, some adaptive control methods have been proposed, such as fuzzy PID methods [12][13][14] and neural network-based PID methods [10,15]. In addition, in order to reduce the impact of time delay, many Smith predictor-based methods are used to modify PID controllers [16,17].…”

Section: Introductionmentioning

confidence: 99%

Grouping Neural Network-Based Smith PID Temperature Controller for Multi-Channel Interaction System

Li,

Yang,

et al. 2024

Electronics

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The thermal vacuum test (TVT) is an important verification process in the development of spacecraft and load. There are often multiple temperature points on the device under test (DUT) that require control. The interaction among multiple channels poses a challenge for temperature control in the TVT. To solve this problem, a multi-channel Smith proportional–integral–derivative (PID) controller based on a grouping neural network (Grouping-NN) is proposed. Firstly, the mathematical derivation for a typical multi-channel temperature control model of the TVT is carried out. Then, the multi-channel interaction system is identified using a Grouping-NN to predict the output temperature of each channel by grouping the hidden layer neurons according to the number of channels. Finally, two Grouping-NNs are utilized to update the Smith predictor, and the time-delay error is fed back to the PID controller, which is used to optimize the control effect of the multi-channel interaction system under high time delay. The proposal is compared with the traditional PID controller and Smith predictor-based PID controller through simulation. The simulation results show that the proposed method has better suppression of overshooting. In addition, the algorithm is verified by controlling the temperature of six channels in a practical thermal vacuum test.

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