Battery Residual Capacity Estimation via Aging-Aware Priority Control
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Solution Overview
Problem
Existing methods for estimating the residual capacity of connected batteries in energy distribution networks are imprecise, require frequent manual interventions, and increase operating costs, while not adequately accounting for battery aging and degradation, leading to unavailability and reliability issues.
Innovation Solution
A method that involves collecting physical quantities to determine battery aging, prioritizing charging and discharging based on aging states, and calculating residual capacity using a stationary storage system that includes a battery supervision system, charger, and inverter, allowing for automated and precise energy management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If periodic manual control interventions are implemented to measure battery characteristics, then battery state information can be obtained, but operating costs increase and battery availability decreases
Solution Approach 1:
The battery management system automatically performs measurements and estimations without manual intervention. The controller continuously monitors battery characteristics and performs self-diagnosis, eliminating the need for periodic manual control operations while maintaining measurement accuracy.
Solution Approach 2:
Manual measurement operations are replaced by an automated electronic control system that continuously monitors battery state using sensors and algorithms, substituting human intervention with automated electronic detection and calculation processes.
2Device complexity
If simple battery charge/discharge control is implemented, then system complexity is reduced, but estimation precision of usable energy deteriorates
Solution Approach 1:
The system uses multiple battery parameters (temperature, voltage, current, state of charge, state of health) to dynamically adjust control decisions. By monitoring and responding to changes in these parameters, the system achieves precise energy estimation and optimization without requiring complex manual intervention procedures.
Solution Approach 2:
The controller continuously monitors battery state and uses feedback from temperature, voltage, current, and state of health measurements to adjust charge/discharge control in real-time, enabling precise usable energy estimation through automated feedback loops rather than simple open-loop control.
3Ease of operation
If battery aging and degradation are not accounted for, then operational simplicity is maintained, but reliability and operational safety deteriorate
Solution Approach 1:
The system performs preliminary assessment of battery state of health and aging characteristics before making operational decisions. By evaluating battery degradation status in advance, the system can adjust control parameters to maintain reliability and safety without requiring complex real-time interventions during operation.
Solution Approach 2:
The battery management system automatically monitors and assesses battery aging and degradation without manual intervention, continuously updating state of health estimates and adjusting control strategies to maintain operational safety while keeping the system easy to operate.
4Ease of operation
If maximum charge levels are not optimized based on aging state, then charging operation is simplified, but loss of energy increases due to degraded battery performance
Solution Approach 1:
The system dynamically adjusts maximum charge levels based on the battery's state of health and aging parameters. By modifying charge control parameters according to measured battery degradation, the system optimizes energy utilization and reduces energy losses in degraded batteries while maintaining simple automated operation.
Data Source
Figure 1
AI summary
This is a method of estimating the residual capacities of a plurality of batteries (50) connected to an electrical energy distribution network (55). The method comprises the following steps: selecting (30, 35) a battery (50) from among said plurality of batteries (50) on the basis of information gathered (20, 25) determining the state of ageing of each of the batteries and/or of information relating to a planning of the use of the batteries and/or of a user directive, during the energy storage phase, charging by priority said battery (50) selected until the attaining of a predefined maximum level of charge dependent on the state of ageing, during the energy destorage phase, discharging by priority said selected battery, if it has attained the maximum level of charge during the storage phase, until the attaining of a predefined minimum level of charge dependent on the state of ageing, then measuring a level of energy drawn (EresChk) by said selected battery (50).