Electrochemical Electric Field Decoupling with Parallel Targeting
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Solution Overview
Problem
Conventional shooting methods for decoupling the electric field in electrochemical models of lithium ion batteries are prone to data overflow and non-convergence due to high dependency on initial trial solutions and long tracking lengths, leading to slow processing speeds.
Innovation Solution
A parallel targeting method is employed, dividing the calculation region into smaller units with (N−1) nodes, using interpolation methods to set initial target values, and iteratively adjusting these values until the target shooting values converge within a preset range, ensuring continuous and smooth targeting curves and preventing data overflow.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional shooting method is used to solve boundary value problems in electric field coupling, then the method has simple principles and high precision in calculation results, but it is highly dependent on initial trial solution and easily leads to intermediate calculation data overflow and failure to converge when tracking length is long
Solution Approach 1:
The patent divides the calculation region into multiple sub-regions with smaller tracking lengths by inserting (N-1) nodes between the two endpoints. This segmentation allows the shooting method to be applied to each smaller sub-region independently, preventing data overflow that occurs in the conventional single-shot approach with long tracking length, while maintaining calculation precision through iterative refinement of target values at the nodes.
2Reliability
If multiple serial shooting is performed to prevent data overflow by reducing tracking length, then data overflow problem is solved, but the processing speed becomes much slower compared to conventional shooting method
Solution Approach 1:
The patent merges the shooting calculations for multiple sub-regions by performing them in parallel rather than sequentially. The target values at internal nodes are iteratively adjusted based on the mismatch between target shooting values and target values, allowing simultaneous optimization of all sub-regions and significantly improving processing speed compared to multiple serial shooting approaches.
Solution Approach 2:
The patent implements a feedback mechanism where the target values of observed quantity at internal nodes are iteratively adjusted based on the difference between target shooting values and target values from previous iterations. This feedback loop continues until the distances between corresponding values are within preset ranges, ensuring convergence while maintaining efficient parallel processing.
3Reliability
If the calculation region is divided into N sub-regions with smaller tracking lengths, then data overflow is prevented and convergence is improved, but the device complexity and computational overhead increase
Solution Approach 1:
The calculation region is segmented into N sub-regions by inserting (N-1) internal nodes, where each sub-region serves as an independent calculation unit. This segmentation reduces tracking length within each unit to prevent data overflow while maintaining overall system manageability through standardized processing of each sub-region.
Solution Approach 2:
The patent changes the parameters of observed quantity (target values at nodes) iteratively to optimize the solution. By adjusting target values based on feedback from parallel shooting results, the method achieves convergence with controlled complexity despite the increased number of calculation units.
Data Source
AI summary
The invention provides a method and system for decoupling electric field of electrochemical model based on a parallel targeting method. The method includes selecting a negative or positive electrode region as a calculation region; selecting a solid or liquid phase current as an observed quantity, and a solid and liquid phase potential as a costate variable; inserting nodes between two endpoints of the calculation region, and determining a target value of the observed quantity of each node; constructing N calculation units; respectively performing a target shooting on the N calculation units; and determining whether a distance between the target shooting value of the observed quantity of the end point of each calculation unit and the target value of the observed quantity of the node corresponding to the end point of the calculation unit is within a preset range.