Vehicle Parameter Estimation Using Temporary Excitation for ADAS
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Solution Overview
Problem
Existing vehicle systems struggle to accurately estimate vehicle parameters such as mass, moment of inertia, and understeer gradient, which are crucial for advanced driver assistance systems (ADAS) like adaptive cruise control and super cruise control. These parameters can change due to various factors, impacting the vehicle's longitudinal and lateral responses.
Innovation Solution
A vehicle parameter estimation system that uses a processor and memory to determine maximum and minimum excitation accelerations. It generates a control input to apply a temporary excitation acceleration to the vehicle, which is then used to estimate vehicle parameters using observation models based on sensor data. These estimated parameters are then transmitted to the ADAS for updating.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a temporary excitation acceleration is applied to the vehicle to improve parameter estimation accuracy, then the measurement precision of vehicle parameters is improved, but the vehicle's longitudinal and lateral responses are altered which impacts ADAS performance
Solution Approach 1:
The system dynamically adjusts vehicle parameters by applying temporary excitation acceleration only during specific estimation periods, allowing the vehicle dynamics to change temporarily for measurement purposes while restoring normal operation for ADAS functionality. This dynamic switching between estimation mode and normal operation mode resolves the contradiction between needing altered dynamics for accurate measurement and maintaining stable dynamics for reliable ADAS performance.
Solution Approach 2:
The excitation acceleration is applied periodically or intermittently rather than continuously, allowing the system to obtain updated parameter estimates at scheduled intervals while maintaining normal vehicle operation between updates. This periodic application of excitation ensures that ADAS features operate reliably with default parameters most of the time, while still benefiting from periodic parameter refreshes to maintain estimation accuracy.
2Reliability
If default vehicle parameters are used to maintain stable ADAS operation, then the reliability of ADAS features is maintained, but the measurement precision of vehicle parameters deteriorates when vehicle conditions change
Solution Approach 1:
The system implements a feedback mechanism where vehicle parameters are periodically re-estimated based on sensor data collected during excitation events. The estimated parameters are then fed back to update the ADAS system, ensuring that the parameters remain current with actual vehicle conditions. This feedback loop resolves the contradiction by maintaining reliable ADAS operation with default parameters while periodically refreshing the parameter estimates to maintain accuracy when vehicle conditions change.
Solution Approach 2:
The system performs preliminary parameter estimation updates during scheduled excitation events before significant vehicle condition changes occur. By proactively updating parameters during controlled excitation periods, the system ensures that accurate parameter values are available before they become outdated, maintaining both reliability during normal operation and precision when conditions change.
Data Source
AI summary
Methods and systems are provided for estimating vehicle parameters of a vehicle. A maximum desired vehicle acceleration and a minimum excitation acceleration in a first direction are determined. The minimum excitation acceleration is associated with generating an estimated vehicle parameter. A first control input for transmission to an advanced driver assistance system (ADAS) to apply a temporary excitation acceleration that is greater than the minimum excitation acceleration and less than the maximum desired vehicle acceleration is generated. The estimated vehicle parameter is generated using a vehicle parameter estimation observation model based on vehicle data received from at least one vehicle sensor. The vehicle data is generated in response to the application of the temporary excitation acceleration to the vehicle. The estimated vehicle parameter is transmitted to the ADAS of the vehicle for replacement of a previous vehicle parameter at the ADAS with the estimated vehicle parameter.