Hybrid Vehicle Controller Load Balancing Across Function Triggers
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Solution Overview
Problem
Conventional vehicle control systems fail to address load imbalance in controllers executing multiple functions dynamically, leading to delays or skips in function execution due to overloading.
Innovation Solution
A control system that balances computational load by dividing functions into subsets and executing them across multiple function triggers, using offline testing data to determine runtimes and assign subsets equally across triggers to minimize load differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the controller executes multiple functions simultaneously based on dynamic operating conditions, then the vehicle control system can respond adaptively to different operating scenarios, but the controller becomes overloaded causing function delays or execution failures
Solution Approach 1:
The patent segments the set of allowed functions into multiple subsets and distributes these subsets across N instances of function triggers. This segmentation prevents any single trigger instance from being overloaded with too many functions, while still allowing the system to execute all necessary functions across multiple triggers, thus maintaining both adaptability and reliability.
2Productivity
If the controller executes all allowed functions in each function trigger instance, then complete functionality is achieved, but computational load becomes unbalanced causing some triggers to be overloaded
Solution Approach 1:
The patent divides the set of allowed functions into multiple subsets and assigns these subsets evenly across N function trigger instances. This ensures that computational load is balanced across all trigger instances, preventing any single instance from being overloaded while maintaining complete execution of all necessary functions across the system.
Solution Approach 2:
The patent dynamically determines the set of allowed functions based on current operating conditions and constraints, then dynamically assigns these functions to subsets and distributes them across N trigger instances. This dynamic approach allows the system to adapt to changing conditions while maintaining balanced computational load distribution.
3Reliability
If the controller prioritizes executing certain functions over others when overloaded, then critical functions can be maintained, but non-critical functions are delayed or skipped causing incomplete operation
Solution Approach 1:
The patent segments functions into subsets distributed across multiple trigger instances, ensuring that critical functions are included in the allowed set based on operating conditions and are executed across the distributed instances. This segmentation approach ensures both critical and non-critical functions are completed without delays or skips.
Data Source
AI summary
A control technique for balancing controller computational processing loads in a vehicle includes determining a set of allowed functions from a plurality of functions executable by the controller based on a set of constraints corresponding to a set of operating parameters of the vehicle, dividing the set of allowed functions into a plurality of subsets to obtain a plurality of subsets of allowed functions, based on offline testing data relating to runtimes of the plurality of functions, equally assigning the plurality of subsets of allowed functions across N instances of the function trigger, wherein N is an integer greater than one, and executing the set of allowed functions across the N instances of the function trigger as equally assigned to balance a computational load on the controller.