Insulation Detection of Electric Vehicles by Using FPGA-Based Recursive-Least-Squares Algorithm

• Published in: World electric vehicle journal Vol. 15; no. 1; p. 25
• Main Authors: Bukya, Mahipal, Malthesh, Shwetha, Kumar, Rajesh, Mathur, Akhilesh
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.01.2024
• Subjects: Algorithms; Compressed gas; electric vehicle; Electric vehicles; Error detection; Feedback; Field programmable gate arrays; FPGA; High voltages; Insulation; insulation detection techniques; Least squares; Lithium-ion batteries; Measurement techniques; Natural gas; Petroleum; Power supply; Rechargeable batteries; recursive mean squares algorithms; Safety; Signal processing
• ISSN: 2032-6653; 2032-6653
• DOI: 10.3390/wevj15010025

The principal reason for why electric vehicles are required to serve as an alternative to the more widespread gasoline and petroleum-based vehicles used in modern times is due to the use of an environmentally conscious means of transportation or to circumvent the tumultuous economic dealings of the compressed natural gas and petroleum industries. There is a growing daily need for large, high-voltage e-mobilities, mostly driven by anticipated advancements in electric vehicle technology. Consequently, all of the various components of these vehicles must be able to be accommodated within a limited and compact space. The battery is an essential component in e-mobility. The insulation, health monitoring, and problem diagnostics of lithium-ion (Li-ion) batteries are of utmost importance in ensuring these vehicles’ safety and efficient functioning. Real-time and fast insulation detection techniques are required to ensure safety in high-voltage (HV) vehicles and to avoid insulation failure. This paper used the Recursive-Least-Squares (RLS) algorithm because it is computationally efficient for building the insulation detection system. Based on the RLS technique, we proposed field programmable gate array (FPGA)-based algorithms and implemented them using VHDL coding. The FPGA is very fast at detection, and the error is lower. We validated the FPGA results with MATLAB simulation results from the existing literature, and the errors are much less when using FPGAs. An experimental hardware platform was also created to validate the proposed FPGA technique with various motor and resistive loadings on electric vehicles (EVs).