IMPROVING THE ACCURACY OF REMOTE DIAGNOSTICS OF A HIGH-VOLTAGE BATTERY

Abstract

The article discusses hardware and software methods for increasing the accuracy of obtaining remote diagnostics (RD) results for high-voltage energy storage (HVES) batteries of electric vehicles (EV). This will ultimately improve the quality of technical operation by promptly identifying problematic cells, planning routine repairs, adjusting maintenance norm, and forecasting the condition of high-voltage energy storage devices to bring them closer to their ideal lifespan. The main focus is on obtaining data without distortion from the effects of electromagnetic interference on board the EV. However, the obtained results can be used to improve the existing systems, as well as to design new ones. The results of remote diagnostics of individual cells and the entire high-voltage battery can be used to adjust operating modes along the route and select routes based on the actual condition to practice the maximum possible number of charge-discharge cycles, improving the culture of drivers, and, in the future, become the basis for application in unmanned control. The work includes an analysis of data reading algorithms and methods for parameter reliability controlling a data packet to eliminate errors when performing calculations both on board the EATS and on a remote control system.