Battery Charge Threshold Control for Voltage Rebalancing
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Solution Overview
Problem
Current energy management systems for storage systems lack accurate control strategies to monitor and maintain battery performance, leading to inefficient operation and reduced lifespan due to prolonged use.
Innovation Solution
An electrical energy management method and software that monitors the state of charge and voltage balance of storage systems, adjusting minimum and maximum state of charge values and performing rebalancing steps to optimize battery performance and extend lifespan.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If battery storage systems operate without accurate control strategies, then operational flexibility is maintained, but battery performance deteriorates and lifespan is reduced
Solution Approach 1:
The system dynamically adjusts operational parameters including state of charge thresholds, charge/discharge rates, and voltage limits based on real-time battery conditions. This allows optimization of both performance and lifespan by adapting parameters to the battery's current state and forecasted conditions
Solution Approach 2:
The control strategy implements continuous monitoring of battery parameters (voltage, current, temperature, state of charge) and uses this feedback to adjust operational decisions. The system compares actual performance against targets and modifies control actions to maintain optimal operation and prevent degradation
2Quantity of substance
If maximum charge capacity is continuously utilized, then energy storage capacity is maximized, but battery degradation accelerates
Solution Approach 1:
The system dynamically adjusts the maximum state of charge threshold based on forecasted energy prices, load conditions, and battery health status. Rather than operating at fixed maximum capacity, the control strategy adapts the charge level to balance energy storage needs with battery preservation, reducing stress during critical periods
Solution Approach 2:
The control strategy proactively limits charge capacity before degradation can occur by predicting future battery stress conditions. Based on forecasts and current state assessment, the system pre-adjusts operational parameters to prevent harmful charge cycles before they damage the battery
3Productivity
If detailed monitoring and control of battery parameters is implemented, then battery performance is optimized, but system complexity increases
Solution Approach 1:
The control system integrates multiple functions into a unified platform that simultaneously performs real-time monitoring, predictive analytics, control optimization, and reporting. This multi-functional approach consolidates what would otherwise require separate systems, managing complexity while enhancing productivity
Solution Approach 2:
The system automatically adjusts control parameters and makes operational decisions based on embedded algorithms and forecasts, reducing the need for manual intervention. The self-adjusting nature handles complexity internally while presenting a simplified interface for users
Data Source
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AI summary
An electrical energy management method for storage systems connectable to the electrical grid (3), comprising a first verification cycle (100) for verifying the state of charge of a storage system (1), comprising the following operating steps: - measuring the maximum state of charge in a predefined moment in time; - verifying whether the measured maximum state of charge (SOCril) is greater or less than a predefined value of the maximum state of charge (SOC_MAX); - if the measured maximum state of charge (SOCril) is less than said predefined value of the maximum state of charge (SOC_MAX), verifying for how long it has been less; - if it has been less for a period of time exceeding a predefined time interval, modifying a usage value of the minimum state of charge (SOC_MIN) of the storage system (1) according to the following formula: Usage value of the minimum state of charge (SOC_MIN) = Predefined value of the maximum state of charge (SOC_MAX) - measured value of the maximum state of charge (SOCril) + Default value of the minimum state of charge (SOCD).