Vehicle dynamics balance point solving method based on particle swarm algorithm

Abstract

The invention discloses a vehicle dynamics balance point solving method based on a particle swarm algorithm. The method comprises the following steps: establishing a vehicle three-degree-of-freedom planar motion differential equation; solving a vehicle three-degree-of-freedom planar motion differential equation based on a phase space method to obtain a phase space trajectory diagram of the three-degree-of-freedom vehicle dynamics simulation model; analyzing a phase space trajectory diagram of the three-degree-of-freedom vehicle dynamics simulation model to determine a solution space of a balance point; initializing parameters of a particle swarm optimization algorithm; constructing a fitness function of a particle swarm optimization algorithm; and based on a particle swarm algorithm, solving in the solution space of the balance point to obtain a system balance point. According to the method, the particle swarm optimization algorithm is used for searching the balance point meeting the target function in the global solution space range, and the problem that the real balance point of the system cannot be quickly and accurately found through a traditional numerical optimization algorithm is solved.

Description

technical field [0001] The invention relates to the field of vehicle nonlinear dynamics analysis, in particular to a method for solving a vehicle dynamics equilibrium point based on a particle swarm algorithm. Background technique [0002] In order to grasp the basic characteristics of vehicle handling stability, the classical handling stability theory establishes a two-degree-of-freedom vehicle model including lateral motion and yaw motion. The premise of the analysis is that the longitudinal motion of the vehicle is not considered (vehicle speed is constant), and it is assumed that the tire only works in the linear region (small side slip angle), that is, the tire lateral force and the tire side slip angle are only a simple linear relationship. This is very convenient for analyzing the steering of the vehicle at low speed or high speed with small turning angle, but it does not consider the actual situation that the steering wheel angle of the vehicle will be very large whe...

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Problems solved by technology

[0004] In order to solve the deficiencies in the prior art, the present invention proposes a method for solving the equilibrium point of vehicle dynamics based on particle swarm optimization. Afterwards, the particle swarm optimization algorithm was used to search for the equilibrium point in line with the objective function within the scope of the global solution space, which solved the problem that the traditional numerical optimization algorithm could not quickly and accurately find the real equilibrium point of the system

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