Predictive SoC Cooling Control for Autonomous Driving Vehicles
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Solution Overview
Problem
Heat generation in systems on chip (SoC) for autonomous driving poses challenges during advanced arithmetic processing, leading to difficulties in maintaining optimal operating temperatures for reliable vehicle control.
Innovation Solution
A cooling execution device that predicts the operation of the SoC based on sensor data and initiates cooling measures, utilizing machine learning models to anticipate temperature changes and adjust cooling methods accordingly, including air, water, and liquid nitrogen cooling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If advanced arithmetic processing is performed in the SoC for autonomous driving, then the autonomous driving function is improved, but heat generation increases causing temperature to rise
Solution Approach 1:
The cooling execution device predicts future operation status of the SoC based on current detection results and initiates cooling measures in advance before the temperature actually rises. The prediction unit uses machine learning models to forecast temperature changes, and the execution unit starts cooling operations proactively, preventing overheating before it occurs during intensive autonomous driving processing.
2Temperature
If cooling measures are continuously applied to the SoC, then temperature control is improved, but energy consumption increases
Solution Approach 1:
The cooling execution device applies cooling measures periodically rather than continuously. The execution unit activates cooling based on predicted temperature changes and deactivates it when temperature stabilizes or the vehicle stops. This periodic cooling approach maintains effective temperature control while significantly reducing energy consumption compared to continuous cooling operation.
3Temperature
If multiple cooling methods (air, water, liquid nitrogen) are available, then temperature control flexibility is improved, but device complexity increases
Solution Approach 1:
The cooling execution device dynamically selects and switches between different cooling methods based on real-time temperature conditions and processing load. The execution unit chooses from air cooling, water cooling, or liquid nitrogen cooling depending on the situation, making the cooling system adaptable to varying thermal demands without requiring all cooling components to operate simultaneously, thus managing complexity through dynamic rather than static configuration.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution effectively maintains optimal operating temperatures for the SoC, enabling advanced arithmetic operations and ensuring reliable autonomous driving by preventing overheating.
Implementation Method 1
a cooling unit that cools the SoC
Data Source
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AI summary
The cooling execution device includes: an acquisition unit that acquires a detection result of detecting an object related to operation of a control device mounted on a vehicle, the control device controlling autonomous driving of the vehicle; and an execution unit that performs cooling of the control device based on the detection result.