Vehicle Axle Weight Distribution Sensing for Autonomous Control
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Solution Overview
Problem
Conventional methods for determining vehicle weight distribution are inaccurate, relying on engine torque, brake torque, and inertial measurement units, which do not provide reliable data for autonomous vehicle control.
Innovation Solution
Utilizing wireless weight scale sensors to measure axle pressures and tire pressure monitoring system (TPMS) sensors to determine vehicle weight distribution, with error detection and removal processes to filter out erroneous data, enabling precise control of vehicle operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods (engine torque, brake torque, inertial measurement units) are used to determine weight distribution, then the system complexity is reduced, but the measurement precision and reliability deteriorate
Solution Approach 1:
The patent combines data from multiple sensor types (axle weight sensors, tire pressure sensors, inertial measurement units) into a unified weight distribution determination system. The control computer integrates readings from these diverse sensors to compensate for individual sensor limitations and achieve more accurate weight distribution measurements than any single sensor could provide alone.
Solution Approach 2:
The patent introduces a control computer as an intermediary that processes and validates sensor data. The control computer performs error detection, removes erroneous values, and reconciles data from multiple sensors to produce accurate weight distribution determinations, acting as a mediator between the physical sensors and the autonomous driving control systems.
2Reliability
If multiple sensors are used to improve measurement accuracy, then the reliability improves, but the device complexity increases
Solution Approach 1:
The patent implements feedback mechanisms where the control computer continuously monitors sensor readings, compares them against expected ranges, and identifies erroneous values. The system uses statistical analysis and cross-validation between sensors to detect inconsistencies and provide feedback for correcting or discarding unreliable measurements, thereby maintaining high reliability despite multiple sensors.
Solution Approach 2:
The patent segments the weight distribution measurement function across multiple independent sensors rather than relying on a single complex sensor. By dividing the measurement task among axle weight sensors, tire pressure sensors, and inertial measurement units, the system achieves redundancy and improved reliability while managing complexity through functional segmentation.
3Measurement precision
If error detection and removal operations are performed on sensor values, then the measurement precision improves, but the processing time increases
Solution Approach 1:
The patent applies partial error detection and removal operations by setting thresholds for when error checking is performed and which sensor values are scrutinized. Not all sensor readings undergo exhaustive validation - the system selectively applies error detection based on plausibility checks and statistical deviations, removing only clearly erroneous values while accepting readings within acceptable ranges to minimize processing time.
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 reliability of vehicle control systems by providing accurate weight distribution data, allowing for optimized braking, gear selection, and steering based on actual load conditions, thereby improving safety and efficiency in autonomous driving.
Implementation Method 1
receiving, from a first set of sensors coupled to axles of a vehicle, a first set of values that indicate weights or pressures applied on axles of the vehicle
Implementation Method 2
receiving, from a second set of sensors coupled to tires or tire wheels of the vehicle, a second set of values that indicate pressures in tires of the vehicle
Data Source
AI summary
Techniques are described for determining weight distribution of a vehicle. A method of performing autonomous driving operation includes determining a vehicle weight distribution that values for each axle of the vehicle that describe weight or pressure applied on a respective axle. The values of the vehicle weight distribution are determined by removing at least one value that is outside a range of pre-determined values from a set of sensor values. The method further includes determining a driving-related operation of the vehicle weight distribution. For example, the driving-related operation may include determining a braking amount for each axle and/or determining a maximum steering angle to operate the vehicle. The method further includes controlling one or more subsystems in the vehicle via an instruction related to the driving-related operation. For example, transmitting the instruction to the one or more subsystems causes the vehicle to perform the driving-related operation.