Vehicle Gradient Estimation Control During Four-Wheel Skidding
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Solution Overview
Problem
Existing vehicle control systems struggle to accurately estimate road surface gradient when all four wheels are skidding simultaneously, leading to difficulties in determining vehicle velocity and gradient due to incorrect wheel velocity detection.
Innovation Solution
The vehicle control device employs a method that includes determining a first difference in rotational angular acceleration between front and rear axles, setting a time constant for a low-pass filter based on this difference, and executing first-order lag processing to estimate the road surface gradient and vehicle velocity, even when all wheels are skidding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wheel velocity detection is used to estimate road surface gradient, then gradient estimation is accurate under normal conditions, but the estimation fails when all four wheels are skidding simultaneously
Solution Approach 1:
The patent introduces an intermediary approach by using rotational angular acceleration data from the motor generator as a mediator when wheel velocity detection fails during skidding. Instead of directly relying on wheel velocity, the system uses motor generator rotational acceleration as an indirect measurement source, processed through integration and filtering to estimate gradient reliably even when wheels are skidding.
Solution Approach 2:
The patent changes the measurement parameter from wheel velocity to motor generator rotational angular acceleration under skidding conditions. By detecting the change in operational parameters and switching to an alternative parameter (rotational acceleration instead of velocity), the system maintains gradient estimation accuracy regardless of wheel skidding state.
2Device complexity
If a fixed time constant is used for low-pass filtering gradient estimation, then the system is simple to implement, but the estimation accuracy deteriorates when wheel conditions change rapidly
Solution Approach 1:
The patent applies dynamics by making the low-pass filter time constant variable rather than fixed. The time constant is dynamically adjusted based on the detected rotational angular acceleration magnitude - larger acceleration values trigger smaller time constants for faster response, while smaller acceleration values use larger time constants for smoother filtering. This dynamic adaptation maintains accuracy under rapidly changing wheel conditions.
Solution Approach 2:
The patent changes the filter parameter (time constant) based on operating conditions. By monitoring rotational angular acceleration and adjusting the time constant accordingly, the system optimizes the balance between filtering smoothness and response speed, preventing deterioration of estimation accuracy during dynamic driving conditions.
Data Source
AI summary
A vehicle control device for a vehicle includes at least one processor and at least one memory coupled to the processor. The processor is configured to execute processing including: determining a first difference, which represents a difference between rotational angular acceleration of a front axle and that of a rear axle; setting a time constant of a low-pass filter to be a value corresponding to a value of the first difference; determining an estimated value of a gradient of a driving road surface, based on a current value of a rate of change of velocity of the vehicle; and executing first-order lag processing for the estimated value of the gradient by using the low-pass filter having the set time constant and updating the estimated value of the gradient to be the value obtained by executing the first-order lag processing as a currently estimated value of the gradient.