Cloud Energy Budget Manager for Vehicle Battery Protection
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Solution Overview
Problem
Existing systems fail to accurately manage and track the energy state of vehicle batteries, leading to potential discharge issues when vehicles are left unused for extended periods, as they lack real-time energy monitoring and dynamic adjustment capabilities, risking battery drain or unnecessary limitation of key-off functions.
Innovation Solution
A cloud-based energy budget manager system that tracks available energy using State of Charge (SoC) and operational data, compares energy budgets for requested features with actual usage, and updates energy estimates based on real-time measurements to ensure sufficient energy is available before initiating functions, thereby preventing battery drain and ensuring key-off functionality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the vehicle battery is left to discharge naturally without periodic recharging, then the vehicle can operate autonomously without user intervention, but the battery state of charge becomes insufficient to restart the vehicle after extended idle periods
Solution Approach 1:
The system performs preliminary actions by proactively managing battery charge levels before complete discharge occurs. The cloud-based energy budget manager monitors battery state of charge and schedules function executions during periods when sufficient energy is available, preventing the harmful state of complete battery depletion that would prevent vehicle restart.
Solution Approach 2:
The system implements continuous feedback loops where the vehicle reports battery state of charge and current draw to the cloud server, which then adjusts energy budget allocations and function scheduling decisions. This feedback mechanism enables dynamic adaptation to changing battery conditions, ensuring restart capability is maintained while allowing autonomous operation.
2Adaptability or versatility
If the system allows all requested functions to execute without energy verification, then functional versatility is maximized, but battery discharge risk increases
Solution Approach 1:
The system performs preliminary energy verification before allowing function execution. The cloud-based energy budget manager checks whether sufficient energy is available in the battery before directing the vehicle to execute requested functions, preventing battery discharge that would compromise restart capability.
Solution Approach 2:
The cloud-based energy budget manager acts as an intermediary between function requests and vehicle execution. It receives function requests, verifies energy availability against the energy budget, and only permits execution when energy constraints are satisfied, thereby mediating between functional versatility and battery protection.
3Reliability
If the system implements strict energy budget verification for all functions, then battery discharge is prevented, but functional availability is unnecessarily limited
Solution Approach 1:
The system implements dynamic energy budget management where the energy budget for functions is not fixed but adapts based on actual battery state of charge measurements. The cloud server continuously updates energy estimates and adjusts which functions can be executed based on current energy availability, making the system both reliable and flexible.
Solution Approach 2:
The system changes the energy budget parameters dynamically based on measured battery state of charge and actual energy consumption of executed functions. By updating energy estimates in the cloud based on real vehicle data, the system adjusts operational parameters to maximize functional availability while maintaining battery charge levels sufficient for restart.
Data Source
AI summary
A storage maintains energy estimates corresponding to function requests for vehicles. A processor of a server is programmed to receive a function request for a vehicle, and direct the vehicle to perform the function request responsive to determining, according to battery information received from the vehicle and an energy estimate corresponding to the function request, that the vehicle has sufficient energy to perform the function request.