Vehicle Speed Estimation With Kalman Filtering and Sensor Blending
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Solution Overview
Problem
Existing vehicle control systems face challenges in accurately estimating speed and acceleration at low speeds due to sensor limitations, leading to discontinuities and instability in control laws for systems like auto-park, ACC, and driverless vehicles, and inaccuracies in acceleration measurements from accelerometers due to factory installation position and external factors.
Innovation Solution
A method involving three speed ranges (low, high, and intermediate mixing) uses a Kalman filter for low speeds and wheel angular sensors for high speeds, with a linear mixing formula to smooth transitions between these ranges, ensuring continuous speed and acceleration estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor-based speed measurement is used above threshold, then measurement precision is improved, but reliability deteriorates below threshold due to sensor limitations
Solution Approach 1:
The patent introduces an intermediary estimation system that bridges the gap between sensor-based measurement and low-speed operation. The estimator uses accelerometer data and vehicle dynamics models to provide continuous speed estimation below the sensor threshold, ensuring reliability without sacrificing measurement precision in the high-speed range.
Solution Approach 2:
The patent segments the speed measurement system into two distinct ranges: a high-speed range using sensor-based measurement and a low-speed range using estimation algorithms. This segmentation allows each subsystem to operate optimally within its designated range, maintaining measurement precision where sensors work and ensuring reliability where estimation is needed.
2Ease of operation
If accelerometer-based acceleration measurement is used, then ease of operation is improved, but measurement precision deteriorates due to offsets from installation position and external factors
Solution Approach 1:
The patent implements feedback mechanisms where the estimated speed and acceleration are continuously refined based on comparisons with sensor measurements when available. The system uses feedback to correct offsets and compensate for external factors affecting accelerometer accuracy, maintaining ease of operation while improving measurement precision.
Solution Approach 2:
The patent changes the parameters used for acceleration measurement by combining accelerometer data with vehicle dynamics models and sensor-based speed measurements. This multi-parameter approach compensates for accelerometer offsets and external factors, improving precision while maintaining the ease of operation provided by accelerometer-based measurement.
3Device complexity
If discontinuous speed estimation is used at low speed, then device complexity is reduced, but stability deteriorates for control laws
Solution Approach 1:
The patent ensures continuity of speed estimation by using estimation algorithms that seamlessly connect with sensor-based measurements at the threshold boundary. The linear mixing formula and gain scheduling maintain continuous and smooth transitions, preventing discontinuities that would destabilize control laws while avoiding excessive system complexity.
4Stability of the object's composition
If linear mixing formula is used in intermediate zone, then stability of speed estimation is improved, but device complexity increases due to additional processing
Solution Approach 1:
The patent applies partial mixing in the intermediate speed zone rather than across the entire speed range. The linear mixing formula is activated only when speed is near the threshold boundary, reducing unnecessary processing complexity while maintaining stability where it is most needed. This selective application balances stability improvement with complexity management.
Data Source
AI summary
A method for estimating the speed of a motor vehicle includes defining a first speed threshold that corresponds to a minimum speed value supplied by a vehicle wheel angular speed sensor, defining a second speed threshold that is greater than the first, estimating low speed values when the vehicle is running below the first speed threshold by using an estimation method of adaptive filtered type, measuring high speed values when the vehicle is running above the second speed threshold by using vehicle speed values supplied by the wheel angular speed sensor, and in the intermediate zone between the first and second speed thresholds, mixing high speed with low speed.