Hybrid Battery Management for Predictive Engine Charging
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Solution Overview
Problem
Conventional battery management systems (BMSs) for vehicles inefficiently use fuel by failing to account for future periods of high renewable energy production, leading to unnecessary activation of internal combustion engines, resulting in wasted fuel and increased carbon emissions.
Innovation Solution
A system that predicts energy surplus or deficit based on renewable energy output, battery state, and geolocation, determining when to activate the internal combustion engine to charge the battery, thereby optimizing the use of renewable energy sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the internal combustion engine is activated to charge the battery, then the battery power capacity is maintained, but fuel consumption increases and carbon emissions are generated
Solution Approach 1:
The system performs preliminary prediction of renewable energy production using weather forecasts and historical data before making charging decisions. This allows the BMS to anticipate future energy availability and schedule engine activation in advance, rather than reacting to current battery state alone, thereby avoiding unnecessary fuel consumption while maintaining reliability
Solution Approach 2:
The system implements a feedback mechanism where the BMS continuously monitors battery state, compares predicted renewable energy production against consumption patterns, and adjusts engine activation decisions accordingly. This closed-loop control ensures the engine runs only when necessary to maintain battery capacity, minimizing fuel consumption while guaranteeing power reliability
2Reliability
If the internal combustion engine is activated frequently, then the battery remains charged, but mechanical equipment wear increases
Solution Approach 1:
By predicting renewable energy production in advance using weather forecasts and historical consumption data, the system can pre-schedule optimal engine activation times. This prevents frequent or unnecessary engine starts while ensuring the battery is charged during periods when mechanical wear is minimized and renewable energy availability is lowest
Solution Approach 2:
The system dynamically adjusts engine activation thresholds based on multiple parameters including predicted renewable energy production, battery state of charge, time of day, and weather conditions. This adaptive parameter adjustment reduces engine activation frequency compared to fixed-threshold systems, thereby extending mechanical equipment life while maintaining adequate battery charge levels
3Object-generated harmful factors
If renewable energy sources are used exclusively, then carbon emissions are reduced, but power supply reliability may be insufficient during low production periods
Solution Approach 1:
The system dynamically balances between renewable energy sources and internal combustion engine generation based on real-time and predicted conditions. During periods of high renewable production, the system maximizes renewable usage to minimize emissions. During low production periods, the system automatically supplements with engine generation to maintain power reliability, creating a flexible hybrid power management strategy
Solution Approach 2:
The BMS continuously monitors both renewable energy production and battery state, using this feedback to determine the optimal mix of renewable and fossil fuel energy sources. This ensures carbon emissions are minimized during high renewable availability while power supply reliability is maintained during low production periods through automatic engine activation when needed
Data Source
AI summary
Provided is a device configured to determine a power capacity of a battery of a vehicle, predict a first set of values indicative of amounts of power to be stored during a time interval by the battery, the power being generated by a renewable energy generator carried by the vehicle, and predict a second set of values indicative of amounts of energy to be consumed from the battery during the time interval based on previous energy consumption by the vehicle. The device is also configured to determine a score based on the power capacity, the first set of values, and the second set of values. The system is also configured to determine whether the score satisfies a threshold and, in response to a determination that the score satisfies the threshold, activate an internal combustion engine to charge to the battery.