Battery Dispatch Control Using SoH and Throughput Metrics
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Solution Overview
Problem
Current methods for determining battery state of health are challenging to use in optimal control algorithms, particularly due to the need for specific characterization and access to physical parameters, and lack a generic, computationally light solution applicable across different battery chemistries.
Innovation Solution
A method using readily available field measurements to estimate battery state of health and operation metrics, incorporating end-of-life values and warranty data from battery catalogs, with linear calculations to determine optimal dispatch and control strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current methods of determining state of health are used, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent extracts only the essential data elements needed for SoH estimation (cycle count, cumulative throughput, average depth of discharge) from the complex battery operation history, separating these key parameters from other irrelevant operational data. This extraction approach maintains measurement precision while significantly reducing the complexity of data collection and processing.
Solution Approach 2:
The patent creates a simplified computational model that copies the essential degradation behavior of batteries through linear relationships based on throughput and cycle metrics. Instead of requiring complex physical characterization, the model uses readily available operational data to estimate SoH, achieving accurate results without extensive testing or specialized equipment.
2Measurement precision
If comprehensive battery characterization is performed, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The system uses battery operational data that the battery essentially records itself during normal operation (cycle counts, throughput, depth of discharge). This self-service approach eliminates the need for external characterization equipment or specialized testing procedures, making the system easy to deploy at any site while maintaining accurate SoH estimation.
3Productivity
If complex control algorithms are used, then productivity is improved, but device complexity increases
Solution Approach 1:
The patent transforms the control problem from requiring complex nonlinear algorithms to using simple linear relationships. By changing the parameters used for control (from detailed electrochemical states to aggregate metrics like cumulative throughput and average depth of discharge), the system achieves optimal control capability with minimal computational requirements.
Data Source
AI summary
Control of power resources based on battery state of health (SoH) and operation metrics includes estimating a SoH of a particular battery using an end-of-life SOH value and a kWh warranty value from battery catalog data and a battery kWh from battery throughput data; estimating battery capacity using the estimated SoH and a rated battery capacity from the battery catalog data; and estimating an allowable monthly throughput using a month warranty value, the kWh warranty value, the battery kWh, and number of operating months. Dynamic discharge cost is calculated using battery replacement cost data, the kWh warranty value, and the battery kWh. An optimal dispatch for operating the particular battery can be determined considering battery degradation using the estimated battery capacity, the estimated allowable monthly throughput, and the dynamic discharge cost. Dispatch commands can be output according to the determined optimal dispatch.