Steering Thermal Prognostics for Predictive Derating Control
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Solution Overview
Problem
Current steering systems, particularly those with SbW and ADAS, fail to detect thermal limits proactively, leading to fluid degradation, seal damage, and reduced system performance, and are unable to predict thermal derating times.
Innovation Solution
Implement a method and system using a fundamental first-order filter to estimate the time remaining for thermal usage limits and predict thermal derating in steering systems by comparing current and previous outputs, utilizing a Duty cycle strategy and dynamic input conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If current steering systems operate without proactive thermal monitoring, then system complexity is reduced, but thermal damage occurs leading to fluid degradation and seal damage
Solution Approach 1:
The system performs preliminary thermal assessment by continuously monitoring temperature trends and predicting future thermal states before damage occurs. The controller estimates time to thermal limits and proactively adjusts duty cycles to prevent fluid degradation and seal damage, rather than reacting after damage has occurred.
Solution Approach 2:
The system implements closed-loop feedback by continuously monitoring thermal conditions, comparing predicted thermal states against safety thresholds, and adjusting duty cycles accordingly. This feedback mechanism enables the system to maintain reliable operation while managing thermal risks dynamically.
2Reliability
If proactive thermal monitoring is implemented, then thermal damage is prevented, but device complexity increases
Solution Approach 1:
The controller performs self-service by using its existing processing capabilities to execute thermal prediction algorithms and duty cycle adjustments without requiring external monitoring systems. The system leverages available sensor data and internal models to autonomously manage thermal risks, minimizing additional hardware complexity.
Solution Approach 2:
The system manages complexity by changing operational parameters (duty cycles) rather than adding physical components. By dynamically adjusting electrical parameters based on thermal predictions, the system achieves thermal protection through software-based control rather than hardware additions.
3Reliability
If duty cycle adjustments are made to manage thermal limits, then thermal derating is prevented, but system performance is reduced
Solution Approach 1:
The system dynamically adjusts duty cycles based on real-time thermal conditions and predicted trends rather than using fixed limitations. This dynamic approach allows the system to maintain maximum performance when thermal conditions permit while preventing derating only when necessary, optimizing the balance between performance and thermal management.
Solution Approach 2:
By predicting thermal limits in advance, the system can make gradual duty cycle adjustments before thermal damage occurs, rather than implementing sudden performance reductions. This preliminary action allows for smoother transitions that maintain performance longer while still preventing thermal derating.
Data Source
AI summary
A method for providing electrical component thermal prognostics includes proactively estimating a time remaining for thermal usage limits for an electrical component of a vehicle, and predicting a time estimate for thermal derating based on a fundamental first order filter response.