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A self-adaptive control method of ecas system for automobile rollover prevention

An adaptive control and anti-rollover technology, which is applied in control devices, neural learning methods, biological neural network models, etc., can solve problems such as immature technology and achieve the effect of saving the cost of anti-rollover

Active Publication Date: 2021-06-04
ZHEJIANG UNIV +1
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Problems solved by technology

The technology of ECAS system applied to anti-rollover is not mature enough

Method used

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  • A self-adaptive control method of ecas system for automobile rollover prevention
  • A self-adaptive control method of ecas system for automobile rollover prevention
  • A self-adaptive control method of ecas system for automobile rollover prevention

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Embodiment Construction

[0049] The present invention will be further described below in conjunction with the accompanying drawings.

[0050] Such as figure 1 As shown, the overall structure of the present invention mainly includes an LTR setting value 101, an error calculation unit 102, an LTR calculation unit 103, a dead zone function 104, an adaptive PD controller 105, a proportional parameter model 106, an improved GRU model 107, and a memory 108 , the control object 109 and the preprocessing module 110 . The inventive method mainly comprises the following steps:

[0051] Step 1: Collect N types of car driving status data and TTR parameter pairs offline (must include tire pressure data and ECAS system airbag pressure data, and steering wheel angle data and acceleration data); build and train multiple gated cyclic neural network fusion The improved gated recurrent neural network model, that is, the improved GRU model 107;

[0052] Step 2, with a certain sampling period (can be taken as 1 ms), si...

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Abstract

The invention discloses an adaptive control method of an ECAS system for anti-rollover of automobiles. First, collect offline data, build and train an improved gated recurrent neural network for predicting the time of vehicle rollover; then, collect vehicle driving state data with a certain sampling period and perform filtering processing; then use a certain update period to use the pre-trained The improved gated recurrent neural network predicts the rollover time of the vehicle, and then updates the proportional coefficient of the adaptive PD controller; at the same time, calculates the vehicle lateral load transfer ratio with a certain control period, and obtains the deviation from the set value, The deviation is then input into the adaptive PD controller for control output; finally, the electromagnetic valve of the automobile ECAS system adjusts the height of the airbag according to the output of the adaptive PD controller. The model and parameters of the invention can be self-adjusted to achieve a better anti-rollover effect; at the same time, it is applicable to many car models, thereby reducing the workload of test engineers and improving the efficiency of loading ECAS systems on cars.

Description

technical field [0001] The invention relates to the technical field of air control, in particular to an adaptive control method of an ECAS system for anti-rollover of automobiles. Background technique [0002] With the development of the automobile industry, the general public has put forward higher and higher requirements for all aspects of automobiles. Among them, automobile safety is the most important aspect, and all automobile technologies must first consider safety. Anti-rollover technology is one of the more important ones in automobile safety performance. [0003] The anti-rollover technologies in the existing literature and actual engineering are mainly the anti-rollover method of the active stabilizer bar based on the mechanical principle and the anti-rollover method of the vehicle based on the differential braking technology. [0004] For example, in the published patent [CN205615298U], a vehicle anti-rollover system is disclosed. Through the stabilizer bar asse...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): B60W50/00G06N3/04G06N3/08
CPCB60W50/00B60W50/0098G06N3/08B60W2050/0043G06N3/045
Inventor 陈积明宋超超陈亮冯跃李传武
Owner ZHEJIANG UNIV
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