Design of a High-Voltage Insulation Resistance Detection System for Commercial Vehicles
Source abstract
Abstract
Based on the safety monitoring requirements of power batteries for new energy commercial vehicles, this study proposes a battery insulation detection method utilizing the bridge method in combination with existing insulation detection techniques. Through optimization and improvement of this methodology, an insulation detection system for new energy commercial vehicle power batteries was developed, along with a dynamic online calculation method for insulation resistance. Comprehensive experimental testing under multiple operational conditions demonstrates that the proposed system achieves a measurement accuracy with errors below 5% for insulation resistance. Furthermore, the system exhibits significant advantages in dynamic real-time monitoring capabilities and operational reliability.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Battery Technologies Research · Electrical Fault Detection and Protection · High voltage insulation and dielectric phenomena
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Information and Electrical Engineering, Hangzhou City University, Hangzhou 310015, China
Hunan New Energy Heavy Truck Power Systems Engineering Technology Research Center, Changsha 410000, China
Hunan Xingbida Wanglian Technology Co., Ltd., Changsha 410000, China
Funding
Zhejiang Provincial Emergency Department Project · Ministry of Science and Technology
References (27)
Show source-provided references
1. A novel method for preparation of macroposous lithium nickel manganese oxygen as cathode material for lithium ion batteries10.1016/j.electacta.2010.12.108 ↗
2. A novel preparation of core–shell electrode materials via evaporation-induced self assembly of nanoparticles for advanced Li-ion batteries10.1039/C5CC05577F ↗
3. The effects of design parameters on the charge-discharge performance of iron-chromium redox flow batteries10.1016/j.apenergy.2016.08.135 ↗
4. Jiang, J., and Ji, H. (2009, January 12–14). Study of insulation monitoring device for DC system based on multi-switch combination. Proceedings of the 2nd International Symposium on Computational Intelligence and Design, Changsha, China.10.1109/ISCID.2009.115 ↗
5. An overview: Modern techniques for railway vehicle on-board health monitoring systems10.1080/00423114.2017.1296963 ↗
6. Adaptive control for estimating insulation resistance of high-voltage battery system in electric vehicles10.1002/ep.12644 ↗
7. Li, H., Li, Z., Lin, F., Chen, Y., Liu, D., and Wang, B. (2012, January 3–7). Measurement and analysis of insulation resistance of metallized polypropylene film capacitor under high electric field. Proceedings of the IEEE International Power Modulator and High Voltage Conference (IPMHVC), San Diego, CA, USA.10.1109/IPMHVC.2012.6518819 ↗
8. Measurement variations of insulation resistance/polarization index during utilizing time in HV electrical machines—A survey10.1016/j.measurement.2014.09.034 ↗
9. PDC measurements to assess machine insulation10.1109/TDEI.2010.5595547 ↗
10. Rui, R., and Cotton, I. (2010, January 6–9). Impact of low pressure aerospace environment on machine winding insulation. Proceedings of the IEEE International Symposium on Electrical Insulation, San Diego, CA, USA.10.1109/ELINSL.2010.5549718 ↗
11. Effects of atmospheric pressure on DC resistance to tracking of polymer insulating materials10.1109/TDEI.2005.1561796 ↗
12. A real-time insulation detection method for battery packs used in electric vehicles10.1016/j.jpowsour.2018.03.018 ↗
13. Insulation Detection of Electric Vehicle Batteries10.1063/1.5041163 ↗
14. Model based insulation fault diagnosis for lithium-ion battery pack in electric vehicles10.1016/j.measurement.2018.09.007 ↗
15. Chiang, Y.-H., and Sean, W.-Y. (2019). Adaptive Control for Estimating Insulation Resistance of High-Voltage Battery System in Electric Vehicles. New Trends in Electrical Vehicle Powertrains, IntechOpen.10.5772/intechopen.75468 ↗
16. State Estimation of Vehicle’s Dynamic Stability Based on the Nonlinear Kalman Filter10.1007/s42154-018-0028-6 ↗
17. Wen, F., Pei, W., Li, Q., Chu, Z., Zhao, W., Wu, S., Zhang, X., and Han, C. (2021). Insulation Monitoring of Dynamic Wireless Charging Network Based on BP Neural Network. World Electr. Veh. J., 12.10.3390/wevj12030129 ↗
18. Electrical Models for EV’s Batteries: An Overview and Mathematical Design of RC Network10.1007/s40031-022-00852-1 ↗
19. Design of an online insulation resistance detection system for electric vehicles using an unbalanced bridge
20. A novel approach of remaining discharge energy prediction for large format lithium-ion battery pack10.1016/j.jpowsour.2017.01.054 ↗
21. Song, C., Shao, Y., Song, S., Peng, S., Zhou, F., Chang, C., and Wang, D. (2017). Insulation resistance monitoring algorithm for battery pack in electric vehicle based on extended Kalman filtering. Energies, 10.10.3390/en10050714 ↗
22. A new method of insulation detection on electric vehicles based on a variable forgetting factor recursive least squares algorithm10.1109/ACCESS.2021.3079332 ↗
23. Bukya, M., Padma, B., Kumar, R., Mathur, A., and Prasad, N. (2024). FPGA-Based VFF-RLS Algorithm for Battery Insulation Detection in Electric Vehicles. World Electr. Veh. J., 15.10.3390/wevj15040129 ↗
24. An insulation resistance detection method in battery management system
25. Design of insulation detection method for electric vehicles based on unbalanced bridge method
26. Discussion on the improvement of insulation resistance performance requirements and test methods for the whole vehicle in the new version of GB 18384
27. Research on the formula for calculating insulation resistance and alternative methods for GB 18384-2020