Road gradient and car state parameter combined estimation method based on parameter estimation error
A technology of parameter estimation and joint estimation, applied in the field of vehicle engineering, which can solve problems such as dependencies
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Embodiment 1
[0079] Embodiment 1: as Figure 1-8 As shown, a joint estimation method of road slope and vehicle state parameters based on parameter estimation error, the specific steps of the method are as follows:
[0080] According to the process described in the above invention, the slope and state parameters of a class of typical medium-sized vehicles are continuously estimated, and the numerical simulation is carried out in Matlab software.
[0081] Step 1. Establish a vehicle longitudinal dynamics model: According to the vehicle dynamics theory and Newton's second law, the vehicle is subjected to force analysis, and the vehicle longitudinal dynamics model can be obtained as follows:
[0082] m v . = F force - mg sin θ - C vf v - C μ mg cos...
Embodiment 2
[0109] Embodiment 2: as Figure 1-8 As shown, a joint estimation method of road slope and vehicle state parameters based on parameter estimation error, the specific steps of the method are as follows:
[0110] According to the process described in the above-mentioned invention, a finite time estimation is carried out for a class of typical medium-sized vehicle driving road surface slope and state parameters, and a numerical simulation is carried out in Matlab software.
[0111] Step 1. Establish a vehicle longitudinal dynamics model: According to the vehicle dynamics theory and Newton's second law, the vehicle is subjected to force analysis, and the vehicle longitudinal dynamics model can be obtained as follows:
[0112] m v . = F force - mg sin θ - C vf v - C ...
Embodiment 3
[0139] Embodiment 3: as Figure 1-8 As shown, a joint estimation method of road slope and vehicle state parameters based on parameter estimation error, first establishes a vehicle longitudinal dynamics model based on vehicle dynamics theory and Newton's second law; then obtains vehicle speed and engine driving force through vehicle sensor measurements , take it as the input of the estimation algorithm; then perform filtering operation on the vehicle longitudinal dynamics model to extract the parameter estimation error; then judge whether the excitation condition is satisfied: if it is satisfied, use the vector containing the parameter estimation error to design the adaptive law estimation Unknown parameter vector; if not satisfied, add random disturbance to the driving force, and return to re-measure; finally calculate the estimated value of road slope, vehicle weight, viscous friction coefficient, rolling friction coefficient and air resistance coefficient through basic mathem...
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