Micro-Value Vehicle Control Architecture for Shared Sensor Data
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Solution Overview
Problem
Modern vehicle control systems are limited by static algorithms that cannot adapt to changing vehicle use conditions, and sensor data is often compartmentalized, preventing ECUs from accessing all relevant data, which hinders the development of advanced control algorithms.
Innovation Solution
A state-driven micro-value architecture that integrates multiple sensors, a data repository, decision tables, and processors to generate micro-value outputs and vehicle control signals, allowing for dynamic vehicle system control and easy updates of micro-value algorithms without altering primary ECU software.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor data processing is limited to predefined conditions with static algorithms, then system reliability is maintained, but adaptability to changing vehicle use conditions deteriorates
Solution Approach 1:
The patent implements dynamic adaptability by allowing the ECU to load and execute different algorithms from memory based on changing vehicle conditions. The system transitions from static predefined algorithms to dynamic selectable algorithms, enabling the control system to adapt its behavior to different driving scenarios while maintaining reliability through controlled execution environments.
Solution Approach 2:
The patent applies preliminary action by pre-storing multiple algorithms in the ECU memory before runtime. These algorithms are prepared in advance for various vehicle conditions and can be selectively loaded and executed based on current sensor data and operational requirements, enabling rapid adaptation without real-time computation overhead.
2Device complexity
If sensor data is compartmentalized within dedicated ECUs for each function, then device complexity is reduced, but information availability to other ECUs deteriorates
Solution Approach 1:
The patent implements universality by enabling the ECU to access and process sensor data from multiple sources beyond its dedicated sensors. The system can load and execute algorithms that utilize data from various sensors across different vehicle systems, making the ECU a multi-functional processing unit that can handle diverse control tasks requiring different sensor inputs.
Solution Approach 2:
The patent introduces an intermediary mechanism in the form of a data repository or memory system that stores sensor data from multiple sources. This intermediary allows ECUs to access required sensor data without direct point-to-point connections, reducing communication complexity while ensuring information availability across the vehicle control network.
3Adaptability or versatility
If hardware changes are made to enable ECUs to access isolated sensor data, then adaptability improves, but device complexity and manufacturing cost deteriorate
Solution Approach 1:
The patent replaces physical hardware modifications with software-based solutions. Instead of changing the physical ECU architecture or adding hardware connections to access isolated sensor data, the system uses software algorithms that can be loaded into existing ECU memory and executed to process data from available sensors, achieving adaptability through firmware updates rather than hardware changes.
Solution Approach 2:
The patent applies parameter changes by modifying the software configuration and algorithm parameters within the ECU to enable access to different sensor data sets. By changing the operational parameters and data source configurations through software rather than hardware, the system achieves enhanced adaptability without increasing device complexity or manufacturing cost.
Data Source
AI summary
A method to assemble and orchestrate elemental value components to accomplish a meaningful higher value. The method including the steps of detecting, by a first sensor, a first vehicle operating parameter, generating, by the first sensor, a first sensor output indicative of the first vehicle operating parameter, populating, by a data pump, a first data repository entry indicative of the first sensor and the first vehicle operating parameter. The method is further operative for generating, by a first processor, a first micro-value output in response to the first data repository entry and a first micro-value algorithm associated with the first sensor, generating, by a concurrent second processor, a first vehicle control signal in response to the first data repository entry, the first micro-value output and a first decision repository table entry associated with the first micro-value output, and controlling, by a vehicle controller, a vehicle in response to the first vehicle control signal.