Road gradient and car state parameter combined estimation method based on parameter estimation error

Abstract

The invention relates to a road gradient and car state parameter combined estimation method based on a parameter estimation error, and belongs to the field of vehicle engineering. The method comprises the steps of firstly establishing a car driving longitudinal kinetic model according to a car kinetics theory and the newton second law; measuring a car speed and a driving force of an engine by virtue of a car-borne sensor, and adopting the measured car speed and the driving force as input quantities of an estimation algorithm; filtering the car driving longitudinal kinetic model, and extracting a parameter estimation error; judging whether an excitation condition is satisfied: estimating an unknown parameter vector by utilizing a vector designing self-adaptive law containing the parameter estimation error if the excitation condition is satisfied; adding random interference to the driving force if the excitation condition is not satisfied, and returning for re-measurement; finally calculating estimated values of a road gradient, car weight, viscous friction coefficient, rolling friction coefficient and air resistance coefficient by virtue of basic mathematical manipulation. By adopting the method, the cost is reduced, the accumulation of measurement noise can be avoided, and the precision is improved; the calculation quantity is reduced.

Description

technical field

[0001] The invention relates to a method for jointly estimating road slope and vehicle state parameters based on parameter estimation errors, and belongs to the field of vehicle engineering. Background technique

[0002] The control effect of modern vehicles not only depends on the performance of the vehicle controller, but also depends on the dynamic parameter changes during the driving process of the vehicle. If some unknown and dynamically changing parameters (such as road gradient, vehicle weight change, wind resistance, etc.) can be accurately measured during the driving process of the car, it will not only improve the control accuracy of the vehicle system, but also provide information reference for safe driving of the car. However, due to limitations in hardware configuration, installation space, and price, it is impossible to install enough sensors to measure the required information comprehensively. For parameter estimation, some information (vehicl...

Images