Connection Fault Diagnosis for Series-connected Lithium-ion Battery Based on Curve Similarity Calculation and Curve Conversion
- Resource Type
- Conference
- Authors
- Ding, Xinchao; Cui, Zhongrui; Cui, Naxin
- Source
- 2022 6th CAA International Conference on Vehicular Control and Intelligence (CVCI) Vehicular Control and Intelligence (CVCI), 2022 6th CAA International Conference on. :1-6 Oct, 2022
- Subject
- Power, Energy and Industry Applications
Robotics and Control Systems
Transportation
Resistance
Lithium-ion batteries
Accelerated aging
Fault location
Electric vehicles
Lithium-ion battery
Connection fault
Fault diagnosis
Edit distance on real-sequence
Charging curve
- Language
In electric vehicles (EVs), the connection faults in lithium-ion battery packs may cause accelerated battery aging and inconsistency. Timely and effective connection fault diagnosis is of great significance to ensure the safe operation of EVs. This paper proposes a connection fault diagnosis method for series-connected battery packs based on the combination of edit distance on real-sequence (EDR) and charging capacity-voltage (QV) curve conversion. The method can determine the location of the faulty cell and the preliminary quantification of fault degree by calculating the similarity of the cell charging curve. Then, by calculating the conversion parameters, the specific connection resistance value can be calculated and distinguished from the internal resistance. A set of experiments were designed on series-connected batteries to simulate the connection faults with different severity. The experimental results show that the method can effectively locate the connection fault and diagnose its severity in the series-connected batteries without complex battery model.