Battery Parameter Determination via Cycling Protocol
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Solution Overview
Problem
Current methods lack a comprehensive and efficient approach for determining battery one-way efficiencies, which are crucial for accurate State of Charge (SOC), State of Energy (SOE), and State of Health (SOH) calculations, especially in advanced battery systems used for renewable energy storage and grid balancing.
Innovation Solution
A novel method involving a battery cycling protocol in constant current (CC) or constant power (CP) mode, where multiple C-rates and D-rates are selected to perform charge-discharge cycles, allowing for the calculation of roundtrip and one-way efficiencies. These efficiencies are then used to determine SOC, SOE, and SOH vectors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple C-rates and D-rates are tested to determine one-way efficiencies, then measurement precision of battery parameters is improved, but loss of time increases due to extensive cycling requirements
Solution Approach 1:
The method performs preliminary comprehensive cycling tests at multiple C-rates and D-rates to establish one-way efficiency characteristics before actual battery operation. This preliminary characterization allows the system to store efficiency data for future SOC, SOE, and SOH calculations without requiring repeated extensive testing, thus resolving the time loss issue while maintaining high measurement precision.
2Reliability
If comprehensive cycling protocols are performed to determine accurate battery parameters, then reliability of battery management is improved, but device complexity increases due to multiple testing modes and calculations
Solution Approach 1:
The method segments the battery characterization process into distinct constant current (CC) and constant power (CP) cycling modes, each with specific C-rates and P-rates. By dividing the comprehensive testing into manageable segments with standardized protocols, the system achieves reliable parameter determination while reducing the perceived complexity through structured organization of test procedures.
Solution Approach 2:
The method systematically varies key parameters including C-rates (0.2C, 0.5C, 1C, 2C), D-rates (0.2D, 0.5D, 1D, 2D), and temperatures (10°C, 25°C, 40°C, 55°C) to comprehensively characterize battery efficiency. This parameter-based approach provides reliable data across operating conditions while maintaining manageable complexity through controlled variation of specific test parameters.
3Adaptability or versatility
If extensive cycling tests at multiple rates and temperatures are performed, then adaptability of battery model to different conditions is improved, but loss of time and resources increases
Solution Approach 1:
The method performs comprehensive adaptive characterization at multiple temperatures (10°C, 25°C, 40°C, 55°C) and rates during initial battery setup. This preliminary action creates a comprehensive efficiency model that adapts to different operating conditions without requiring additional testing during actual battery operation, thus achieving high adaptability while minimizing time loss.
Data Source
Figure 1A~1B
Figure 2A~2B
AI summary
A method for experimental determination of battery parameters is disclosed. The method comprises the following steps: the determination of multiple roundtrip battery efficiencies for a number of different pairs of charging and discharging battery C-rates / P-rates, solving a nonlinear optimisation problem to obtain one-way efficiencies, and finding a charging and discharging characteristics for selected charging and discharging C-rates / P-rates. The obtained characteristic curves reveal the actual current/power that is charged/discharged into/from the battery when the battery is charged/discharged with selected current/power from/to an external source/sink. This characteristic charging/discharging curves are used for determination of battery charge capacity, battery energy capacity, state-of-charge (SOC), state-of-energy (SOE), state-of-health (SOH) and other important battery parameters. The above method is useful in optimizing operation of a battery energy storage performing energy arbitrage in the day-ahead energy markets.