{"title":"A Compound Self-Heater for Lithium-Ion Batteries at Low Temperature Based on Electromagnetic Induction","authors":"Yue Wang;Yunlong Shang;Lu Mao;Shiyu Wang;Xiangjun Li;Chenghui Zhang","doi":"10.1109/TIE.2024.3488365","DOIUrl":null,"url":null,"abstract":"At low temperature, it is challenging for existing battery heating methods to simultaneously achieve efficient and safe self-heating. For this reason, a compound self-heater (CSH) based on electromagnetic induction is proposed, which is capable of heating batteries safely and efficiently without an external power supply. Particularly, a pulse width modulation (PWM)-driven inductor capacitor (LC) parallel oscillation topology and a special inductive winding structure are proposed, to achieve the combined heating of noncontact electromagnetic induction heating and battery internal ohm heating. Further, the heating topology operation principle is revealed and the electrothermal model (ETM) is developed, providing theoretical guidance for the optimal design of the heater and the development of the heating strategy. The experimental results verify the validity of the CSH and ETM. In the full SOC range, the average heating rate of the CSH is 9.1 °C/min, and the battery can be heated from −20 to 0 °C in 100 s, with only 2.3% of battery energy consumed. Moreover, compared to existing discharge and alternating-current heating methods, the CSH is shown to exhibit better generalizability on LiFePO<sub>4</sub> (LFP) and nickel–cobalt–manganese (NCM) batteries.","PeriodicalId":13402,"journal":{"name":"IEEE Transactions on Industrial Electronics","volume":"72 6","pages":"5982-5992"},"PeriodicalIF":7.2000,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Industrial Electronics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10750828/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
At low temperature, it is challenging for existing battery heating methods to simultaneously achieve efficient and safe self-heating. For this reason, a compound self-heater (CSH) based on electromagnetic induction is proposed, which is capable of heating batteries safely and efficiently without an external power supply. Particularly, a pulse width modulation (PWM)-driven inductor capacitor (LC) parallel oscillation topology and a special inductive winding structure are proposed, to achieve the combined heating of noncontact electromagnetic induction heating and battery internal ohm heating. Further, the heating topology operation principle is revealed and the electrothermal model (ETM) is developed, providing theoretical guidance for the optimal design of the heater and the development of the heating strategy. The experimental results verify the validity of the CSH and ETM. In the full SOC range, the average heating rate of the CSH is 9.1 °C/min, and the battery can be heated from −20 to 0 °C in 100 s, with only 2.3% of battery energy consumed. Moreover, compared to existing discharge and alternating-current heating methods, the CSH is shown to exhibit better generalizability on LiFePO4 (LFP) and nickel–cobalt–manganese (NCM) batteries.
期刊介绍:
Journal Name: IEEE Transactions on Industrial Electronics
Publication Frequency: Monthly
Scope:
The scope of IEEE Transactions on Industrial Electronics encompasses the following areas:
Applications of electronics, controls, and communications in industrial and manufacturing systems and processes.
Power electronics and drive control techniques.
System control and signal processing.
Fault detection and diagnosis.
Power systems.
Instrumentation, measurement, and testing.
Modeling and simulation.
Motion control.
Robotics.
Sensors and actuators.
Implementation of neural networks, fuzzy logic, and artificial intelligence in industrial systems.
Factory automation.
Communication and computer networks.