Four-wheel independent drive electric vehicle reference vehicle speed fault-tolerant adaptive estimation method

Abstract

The invention relates to a four-wheel independent drive electric vehicle reference vehicle speed fault-tolerant adaptive estimation method. A robust adaptive Kalman filtering reference vehicle speed estimation module and a reference vehicle speed estimation module based on rule logic are selected for estimation, wherein the reference vehicle speed estimation module based on the rule logic is usedas a backup of the robust adaptive Kalman filtering reference vehicle speed estimation module, and when Kalman filtering diverges, Kalman filtering can be replaced by a method based on the rule logicto be output; the method is small in dependence on preset parameters, high in estimation precision, good in working condition adaptability and high in fault-tolerant capability, vehicle speed estimation under various complex working conditions such as wheel locking, slipping, ramp driving and steering driving can be achieved, the function safety requirement of automobile control system software design is met, and reliability is effectively guaranteed.

Description

Technical field [0001] The invention relates to a reference vehicle speed fault-tolerant adaptive estimation method for a four-wheel independent drive electric vehicle, which belongs to the field of new energy vehicle design and manufacturing. Background technique [0002] The four-wheel independent drive electric vehicle with in-wheel motor as the power unit has become one of the industry’s recognized future electric vehicle development directions with its simplified chassis structure, fast torque response and accurate control execution; longitudinal vehicle speed is the electric vehicle chassis control The important status information in the vehicle controller has important reference value for the pedal signal analysis of the vehicle controller, the anti-skid (anti-lock) control of the wheels, and the torque distribution strategy. Therefore, the automotive industry also refers to the longitudinal vehicle speed as the “reference vehicle speed”. ; Constrained by factors such as m...

AI Technical Summary

Problems solved by technology

[0003] At present, there are two main ideas for the reference speed estimation method for four-wheel drive vehicles; the rule-based estimation method represented by the dynamic slope method is essentially an empirical method for intuitively dealing with the physical characteristics of the problem, and its advantage lies in its high reliability. , but the estimation accuracy is average and there is no effective countermeasure against measurement noise; in order to make full use of the prior noise statistical characteristics to achieve high-precision estimation of reference vehicle speed, Kalman filter technology has received widespread attention worldwide

However, the reference vehicle speed estimation method based on the classic Kalman filter design requires high modeling accuracy of process noise and measurement noise. This method is not applicable when the wheels are slipping or locked, and the filter divergence caused by model mismatch makes The working condition adaptability of the classic Kalman filter is extremely fragile, and it is difficult to meet the application requirements of automotive products

Generalized vehicle state Kalman filter observers based on nonlinear dynamic equations, such as extended Kalman filter, unscented Kalman filter and other methods rely on accurate modeling of vehicle dynamics and tire forces, and such generalized estimation methods are used to calculate the matrix The dimensionality is usually very high, and it is often necessary to solve the Jacobian matrix online, which imposes harsh conditions on the computing power of the on-board controller, which undoubtedly hinders the engineering application of this technology

[0004] In addition, system failures will inevitably occur during the use of auto parts. The existing technology does not fully consider the sensor failure, abnormal signal value and communication error, and the reliability of the system needs to be improved; at the same time, it must be clearly recognized that the traditional The wheel speed information of the four-wheel drive vehicle can only be obtained through the wheel speed sensor. For the four-wheel independent drive electric vehicle driven by the hub motor, the motor speed information fed back by the motor controller can also be used to estimate the reference speed

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