Vehicle fault pre-judgment system, method and device for electric vehicle leasing operation platform

Abstract

The invention belongs to the field of new energy vehicle fault pre-judgment, particularly relates to a vehicle fault pre-judgment system, method and device for an electric vehicle leasing operation platform, and aims to solve the problem. The system comprises: a fault diagnosis expert knowledge base which is used for storing expert experience data, experiment data and historical data; the information acquisition module that is used for acquiring platform vehicle operation data in real time; the fuzzy logic module that is used for carrying out structural knowledge expression on a fuzzy relationship between the vehicle fault symptoms and the fault causes to obtain a fuzzy rule base; and the fault reasoning module that is used for obtaining a vehicle fault pre-judgment result through a vehicle fault pre-judgment network based on the platform vehicle operation data and the data of the fault diagnosis expert knowledge base. According to the invention, possible faults of the electric vehiclecan be predicted and diagnosed, early warning is timely emitted, an employer is reminded of vehicle faults, accidents are avoided, the pre-judgment cost is low, and the accuracy and precision are high.

Description

technical field [0001] The invention belongs to the field of new energy vehicle failure prediction, and in particular relates to a vehicle failure prediction system, method and device for an electric vehicle rental operation platform. Background technique [0002] Electric vehicles are vehicles powered by power batteries and driven by motors, and require all indicators to comply with road traffic and safety regulations. With the widespread application of electric vehicles, the fault prediction technology of electric vehicles, especially the battery fault prediction technology, has great benefits for the driving safety and operation management of driving users, so more and more people pay attention to it. Among the methods, decision trees, Bayesian networks, fuzzy mathematics, Kalman filtering, and artificial neural networks are widely used. However, the complexity and uncertainty of faults often make fault diagnosis or prediction based on a certain method ineffective. [0...

AI Technical Summary

Problems solved by technology

[0004] In order to solve the above-mentioned problems in the prior art, that is, the complexity and uncertain factors of the faults in the existing electric vehicle field lead to the high cost of vehicle fault prediction and low accuracy and precision, the present invention provides an electric vehicle rental operation Platform vehicle failure prediction system, the vehicle failure prediction system includes the following modules:

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