Selective Free-Rolling for Accurate Heavy-Vehicle Speed Estimation
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Solution Overview
Problem
Existing methods for determining vehicle speed over ground in heavy-duty vehicles are unreliable and costly, particularly in challenging environments, and do not effectively account for wheel slip, leading to sub-optimal control performance and accuracy.
Innovation Solution
A VMM system that combines wheel speed sensors and IMUs to estimate vehicle motion state, models errors in the estimation, and selectively places wheels in a reduced slip condition to maintain accurate speed determination, using mathematical optimization to coordinate MSD actuation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If wheel speed sensors are used to determine vehicle speed over ground, then the measurement is straightforward and cost-effective, but the accuracy deteriorates in low friction conditions, split friction conditions, and during maneuvering involving large wheel forces due to wheel slippage
Solution Approach 1:
The patent introduces an intermediary mechanism (selective free-rolling control) between the wheel speed sensor and the vehicle speed determination. By temporarily reducing wheel slip through controlled free-rolling, the system creates intermediate measurement conditions that allow accurate speed determination even when normal operation would cause slippage. This mediator approach resolves the contradiction by improving measurement accuracy without changing the cost-effective sensor setup.
Solution Approach 2:
The system implements periodic selective free-rolling of wheels to obtain accurate speed measurements. By alternating between normal driven conditions and controlled free-rolling measurement conditions, the system periodically resets the measurement accuracy without requiring continuous expensive alternative measurement systems. This periodic action maintains cost-effectiveness while improving overall measurement precision.
2Measurement precision
If wheel slip is reduced by placing wheels in free-rolling condition, then the accuracy of vehicle speed over ground determination is improved, but the control performance and responsiveness of the motion support devices deteriorates
Solution Approach 1:
The system dynamically adjusts wheel slip conditions based on operational needs. Rather than maintaining constant free-rolling for accurate measurement or constant driven condition for performance, the system transitions between states: normal driven operation for control responsiveness, and selective free-rolling briefly activated when measurement accuracy becomes compromised. This dynamic adaptation resolves the contradiction by optimizing the trade-off between measurement precision and control productivity in real-time.
Solution Approach 2:
The system uses the wheel speed sensors themselves to detect when measurement accuracy is deteriorating due to wheel slip, and automatically triggers corrective free-rolling action. The system serves its own measurement function by self-diagnosing accuracy degradation and self-correcting through controlled free-rolling, eliminating the need for external intervention or continuous performance sacrifice.
3Adaptability or versatility
If IMU and wheel speed sensors are combined to estimate vehicle speed over ground, then the measurement coverage is improved, but the error in the estimated vehicle motion state increases due to integration drift and sensor errors
Solution Approach 1:
The system implements feedback control by continuously monitoring wheel slip conditions and using this information to determine when to activate selective free-rolling. The feedback loop detects when IMU-based estimation accuracy is degrading due to wheel slip, and triggers corrective measurement actions. This feedback mechanism resolves the contradiction by maintaining measurement coverage through multiple sensors while actively correcting for their accumulated errors through selective free-rolling validation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the accuracy and efficiency of vehicle speed estimation and control by reducing wheel slip, allowing for faster and more precise actuator control, especially in environments with low friction or maneuvering conditions.
Implementation Method 1
The rotation speed of the wheel can be reliably obtained from sensors such as Hall effect sensors or rotary encoders.
Implementation Method 2
An inertial measurement unit (IMU) provides data on acceleration and rotation, which can be integrated in order to obtain information about the vehicle speed over ground.
Data Source
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AI summary
A vehicle motion management, VMM, system (360) for a heavy-duty vehicle (100), the system comprising at least one wheel speed sensor (106) configured to output a wheel speed signal indicative of a rotation speed of a respective wheel (102) on the vehicle (100), at least one inertial measurement unit, IMU, (110) configured to output an IMU signal indicative of an acceleration of the vehicle (100), a motion estimation function configured to estimate a vehicle motion state (s) comprising vehicle speed over ground, based at least in part on the wheel speed signal and at least in part on the IMU signal, and a motion support device, MSD, coordination function configured to coordinate actuation of a plurality of MSDs of the heavy-duty vehicle in dependence of a vehicle motion request and the vehicle motion state (s), where the motion estimation function is arranged to model an error in the estimated vehicle motion state (s), and to output a free-rolling request to the MSD coordination function in case the modelled error fails to meet an acceptance criterion, where the MSD coordination function is arranged to reduce a wheel slip set-point of one or more wheels (102) of the heavy-duty vehicle (100) in response to receiving the free-rolling request from the motion estimation function.