Fault Detection Method for New Energy Vehicle Power Battery Signal Based on Sensor Information Fusion
As a new product of energy conservation and environmental protection, new energy vehicles have good prospects. Their internal power battery is the main power source of new energy vehicles. However, due to the fact that the battery engine is a complex system, it can cause malfunction problems in harsh environments. If the power battery of a new energy vehicle malfunc-tions, it will not only degrade the system performance of the vehicle, but also cause catastrophic consequences. Therefore, a fault detection method for the power battery signal of new energy vehicles based on sensor information fusion is studied. The sensor data of the battery system is sorted by the law of consistency, and then the power battery signal of new energy vehicles is estimated in the approximate probability and frequency. The entropy weight method theory is selected to distinguish the data signals, with the single time voltage as the evaluation index, and the judgment signal fault matrix is constructed after pre-processing. The abnormal signal is determined through the fault judgment matrix;the weight is revised under the sensor information fusion algorithm;the signal output is detected by the maximum error range; the signal failure of the new energy vehicle power battery is detected, and the detection method design is completed. The experiment takes four different types of new energy vehicles as test objects, simulates the motion conditions of their power batteries, obtains fault voltage signals at different interfaces, and completes detection testing. The designed battery signal fault detection method can achieve accurate fault signal tracking and achieve more accurate fault signal detection, which has certain application value.
new energy vehiclespower battery signalfault detectionsensor information fusion
万方数据
维普
