Fault diagnosis method and system for electric driven traffic tool

Abstract

The invention discloses a fault diagnosis method and system for an electric driven traffic tool. The method comprises the steps of obtaining running parameter data of a battery of a monitored traffic tool, and performing screening arrangement on the running parameter data to obtain a data matrix of voltages of battery cells; adopting a 3 sigma multi-level screening algorithm for the data matrix to obtain a fault quantity of each battery cell; calculating a fault probability of each battery cell according to the fault quantity; and judging whether the fault probability of each battery cell exceeds a second given value or not, and if yes, judging that the fault occurs. According to the method and the system, a probability characteristic of Gaussian distribution is combined with a 3 sigma confidence interval to form 3 sigma multi-level screening; for low-order fault data, all data exceeding the 3 sigma confidence interval can be removed by one-time screening; and multi-order fault data or fault data with relatively large order-of-magnitude difference can be screened for multiple times and removed to obtain a central value closest to real data, so that the processing efficiency is high.

Description

technical field [0001] The invention relates to the field of fault diagnosis, in particular to a fault diagnosis method and system for an electric drive vehicle. Background technique [0002] During the statistical process of cell voltage of electric drive vehicles, cell voltage faults may occur, resulting in abnormal voltage of individual cells, resulting in deviations in the statistical calculation of the central value. Therefore, when an electric vehicle performs battery data processing, there may be some fault data far away from the central value in the obtained data due to the abnormal voltage of individual cells. When we want to get the central value of a set of data, these fault data will always interfere with the calculation of the real central value, thereby affecting the fault analysis. [0003] In addition, most of the traditional fault analysis is to find the fault first, find the cause of the fault after finding the fault, and then find out the definite relatio...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a fault diagnosis method and system for electric-driven vehicles, establish a 3σ multi-level data screening model, use the probability characteristics of Gaussian distribution, conduct centralized screening of non-fault data, and efficiently and accurately locate fault data And eliminated, it has solved the traditional problem of complex coupling between parameters, difficult modeling, and affecting the timeliness of data processing

Images