Suspension Damping Control Using Navigation Gyro State Estimation
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Solution Overview
Problem
Existing vehicle motion state estimation systems face accuracy issues due to reliance on estimated values from Kalman filters, leading to reduced precision in estimating the vehicle body state.
Innovation Solution
A vehicle control apparatus and suspension system that utilizes wheel speed sensors and a damping force variable shock absorber, integrating information from non-dedicated in-vehicle systems like navigation apparatuses to enhance state estimation accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a Kalman filter is used to estimate vehicle body state using wheel speed sensor data, then the system can operate without dedicated suspension sensors, but the estimation accuracy deteriorates due to reliance on calculated values rather than direct measurements
Solution Approach 1:
The patent combines sensor data from multiple independent systems (wheel speed sensor from braking system, steering angle sensor from steering system, acceleration sensor from inertial measurement system) to estimate vehicle body state. This merging of data sources from different functional systems improves estimation accuracy without requiring a dedicated suspension sensor system.
Solution Approach 2:
The patent utilizes sensors that serve multiple functions: the wheel speed sensor is primarily for braking control but also provides data for suspension estimation; the steering angle sensor is for steering control but also helps estimate body attitude; the acceleration sensor is for stability control but also provides vertical motion information. This multi-functional use of existing sensors resolves the contradiction by avoiding dedicated suspension sensors while maintaining accurate estimation.
2Adaptability or versatility
If estimated values from Kalman filter are used as observed values, then the system can function with existing sensors, but the accuracy of vehicle body state estimation deteriorates due to noise and calculation errors
Solution Approach 1:
The patent implements a feedback mechanism where the estimated vehicle body state (including vertical position, attitude angle, and acceleration) is continuously updated by comparing with actual sensor measurements. The estimation is refined by feeding back the difference between estimated and measured values, reducing the accumulation of errors and noise that would otherwise degrade accuracy.
Solution Approach 2:
The patent introduces an intermediary estimation process that acts as a mediator between raw sensor data and final control decisions. Rather than directly using noisy sensor readings or purely calculated values, the system uses an intermediary state estimation that filters and reconciles data from multiple sources, providing a more accurate representation of the vehicle body state for control purposes.
Data Source
AI summary
A controller estimates a state of a vehicle based on a wheel speed sensor provided on the vehicle, and outputs a control signal to a shock absorber provided between a wheel and a vehicle body according to the estimated state of the vehicle. The controller uses information of a sensor of an in-vehicle apparatus other than an apparatus dedicated to the shock absorber as an observed value in the estimation of the state of the vehicle. In other words, the controller uses sensor information of a navigation apparatus corresponding to the in-vehicle apparatus other than the shock absorber, more specifically, gyro information meaning information of a gyro sensor mounted on the navigation apparatus as the observed value in the estimation of the state of the vehicle.