功率需求驱动的电动载运装备用动力电池充放电能力预测方法

Translated title of the contribution: Power Demand-driven Battery Charging and Discharging Capability Prediction Method for Electric Vehicles

Rui Xiong*, Liangji Yan, Ju Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

The accurate evaluation of charging and discharging power capability is the basis of safe and efficient operation of the batteries and electric vehicles. Aims at electric transport equipment, the main works are as follow. A battery model with input/output power as the control target is established, and the charging and discharging behaviour of battery-driven by power demand is described. A multi-step power prediction method has been proposed through setting a fixed charge-discharge cut-off control voltage to a dynamic control objective, and the detailed prediction strategy for the charging and discharging power capacity has been established. Considering the influence of the state of charge, temperature, and duration, etc, the power update model is established with the long- and short-term memory neural network to improve the prediction performance of battery charge and discharge power capability. The results show that the proposed method can take into account the prediction accuracy and calculation efficiency, and the maximum error is less than 3%; the power correction method can reasonably predict the power capacity under the full state of charge range, wide temperature, and long duration. The error is less than 3%, and the root mean square error is less than 1%.

Translated title of the contributionPower Demand-driven Battery Charging and Discharging Capability Prediction Method for Electric Vehicles
Original languageChinese (Traditional)
Pages (from-to)161-171
Number of pages11
JournalJixie Gongcheng Xuebao/Chinese Journal of Mechanical Engineering
Volume57
Issue number20
DOIs
Publication statusPublished - 20 Oct 2021

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