Method for optimizing parameters of four-driving electric car state observer based on genetic algorithm

A state observer and genetic algorithm technology, applied in the field of vehicle state estimation, can solve problems such as difficulty in adjusting the parameters of the state observer, and achieve the effect of ensuring accuracy

Active Publication Date: 2016-09-21
JILIN UNIV
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Problems solved by technology

[0005] In order to solve the difficult problem of adjusting the parameters of the electric vehicle state observer, the present invention provides a method for optimizing the parameters of the four-wheel drive ele

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  • Method for optimizing parameters of four-driving electric car state observer based on genetic algorithm
  • Method for optimizing parameters of four-driving electric car state observer based on genetic algorithm
  • Method for optimizing parameters of four-driving electric car state observer based on genetic algorithm

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Embodiment Construction

[0030] The technical solution proposed by the present invention will be further elaborated and described below in conjunction with the accompanying drawings.

[0031] The invention provides a method for optimizing the state observer parameters of a modular four-wheel drive electric vehicle based on a genetic algorithm. The method includes the following steps:

[0032] Step 1. Establish a vehicle single-wheel rolling model and a simplified vehicle three-degree-of-freedom model

[0033] 1. Establish a vehicle single-wheel rolling model

[0034] To design the longitudinal tire force sliding mode observer, the vehicle system is simplified as figure 1 The vehicle shown rolls on a single wheel.

[0035] Depend on figure 1 The single-wheel rolling dynamics equation can be obtained as shown in formula (1):

[0036] J ω · i = - R e f ...

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Abstract

The invention discloses a method for optimizing parameters of a four-driving electric car state observer based on a genetic algorithm. By means of the method, the problem that parameter adjustment of an electric car state observer is difficult is solved. The method includes the following steps of building a car single-wheel rolling model and a simplified three-degree-of-freedom car model, designing a longitudinal tire force observer through a sliding-mode observer method with the wheel rotation angular velocity and driving moment of measurement information of a car sensor as input, designing a front shaft lateral tire force sliding-mode observer and a rear shaft lateral tire force sliding-mode observer correspondingly with the estimated longitudinal tire force value, the front wheel rotation angle, the lateral acceleration and the yaw velocity as input, finally designing a car speed full-dimension state observer with the estimated longitudinal and lateral tire force values, the longitudinal and lateral accelerations, the yaw acceleration and the front wheel rotation angle of a car as input, and carrying out observer parameter optimization on estimation modules through the genetic algorithm on the basic of the designed modular car state observer.

Description

technical field [0001] The invention relates to a parameter optimization method for a state observer of a modular four-wheel drive electric vehicle based on a genetic algorithm, and belongs to the technical field of vehicle state estimation. Background technique [0002] As a representative of new energy vehicles, electric vehicles have obvious advantages in terms of cleanliness, environmental protection, and energy saving compared with traditional vehicles powered by gasoline combustion. Therefore, the number of electric vehicles is increasing year by year, and its handling stability and active safety issues have also received extensive attention. [0003] The active safety control system of electric vehicles can effectively improve vehicle handling stability, thereby reducing the occurrence of traffic accidents. The prerequisite for the effective implementation of its various control logics is to accurately obtain the driving status information of the vehicle. However, d...

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Application Information

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IPC IPC(8): B60W40/00B60W40/10B60W40/109B60W40/112B60W40/105
CPCB60W40/00B60W40/10B60W40/105B60W40/109B60W40/112B60W2520/00B60W2520/105B60W2520/12B60W2720/00B60W2720/10B60W2720/12
Inventor 郭洪艳麻颖俊郝宁峰陈虹
Owner JILIN UNIV
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