Dynamic Redundancy Management in Vehicle Data Processing Units
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Solution Overview
Problem
Existing vehicle data processing systems face challenges in achieving high availability and energy efficiency due to redundant systems that consume excessive energy, especially in non-critical vehicle states like parking, where redundancy is not required.
Innovation Solution
A method where one data processing unit can autonomously switch off redundancy by removing execution notes or entering an idle state, reducing power consumption, and switching back on as needed based on vehicle operating states, using sensors and data transmission protocols like Ethernet for efficient energy management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If redundant data processing units are kept active to maintain high availability, then system reliability is improved, but energy consumption increases
Solution Approach 1:
The patent implements dynamic switching between redundant and non-redundant operating modes based on vehicle state. The control unit monitors vehicle operating conditions and automatically activates or deactivates the second data processing unit, transitioning the system from a static redundancy configuration to a dynamic one that adapts to current operational requirements, thereby reducing energy consumption when full redundancy is not needed.
Solution Approach 2:
The system changes the operational parameter of the second data processing unit between two states: fully active (100% power consumption) and deactivated (0% power consumption). This binary parameter change allows the system to optimize energy consumption by switching off the redundant unit during non-critical vehicle states while maintaining availability during critical operations.
2Reliability
If both data processing units execute all processes, then computational redundancy is maximized, but computing resource utilization increases unnecessarily
Solution Approach 1:
The patent extracts the execution of specific processes from the second data processing unit by removing corresponding entries from its process list. The control unit identifies which processes should be executed by the first unit and removes these from the second unit's workload, leaving only critical processes that require redundant execution. This selective extraction optimizes computing resource utilization by preventing duplicate execution of non-critical processes.
Solution Approach 2:
Instead of fully activating or fully deactivating the second data processing unit, the system applies partial action by selectively removing only certain process entries from the second unit's process list. This allows the second unit to maintain execution of critical processes for fault tolerance while avoiding the excessive computation of non-critical processes, achieving an optimal balance between reliability and resource efficiency.
Data Source
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AI summary
A method for operating at least two data processing units (VCC1, VCC2) with high availability, in particular in a motor vehicle, is explained. A first data processing unit (VCC1) and a second data processing unit (VCC2) can each provide the same function to an extent of at least 60 per cent or at least 90 per cent. The second processing unit (VCC2) automatically removes at least one indicium (120, 122) for a process to be executed from a memory unit or automatically puts itself into a standby mode.