Battery Management System Using Moving Horizon Estimation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Rechargeable lithium batteries experience capacity reduction due to undesirable side reactions during repeated charge/discharge cycles, leading to reduced power storage and extended charge times when traditional methods attempt to minimize these effects.
Innovation Solution
A battery management system employing a Moving Horizon Estimation method that estimates battery states and parameters using electrochemical-based models and differential algebraic equations to regulate charging and discharging, optimizing battery operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the rate of charge/discharge is limited to minimize side reactions, then battery capacity and performance are preserved, but charge time increases and peak power is reduced
Solution Approach 1:
The battery management system dynamically adjusts charge/discharge rates based on real-time estimation of battery states (state of charge, state of health, temperature) rather than using fixed limited rates. This allows the system to optimize between minimizing side reactions and maintaining acceptable charge times by adapting the charge rate to current battery conditions.
Solution Approach 2:
The system uses feedback from sensors measuring voltage, current, and temperature to continuously update the electrochemical model and adjust charging parameters. This closed-loop control enables the system to respond to actual battery conditions, preventing excessive side reactions while avoiding unnecessary charge time extension.
2Reliability
If the rate of charge/discharge is limited to minimize side reactions, then battery capacity is preserved, but peak power is reduced
Solution Approach 1:
The system dynamically determines allowable charge/discharge rates based on real-time battery state estimation, allowing peak power to be achieved when battery conditions permit while preventing side reactions when conditions are unfavorable. This replaces static power limiting with adaptive power management.
Solution Approach 2:
The system changes operational parameters (charge rate, voltage, current) based on estimated battery states from the electrochemical model. By adjusting these parameters dynamically, the system maintains peak power capability when safe while reducing rates when side reactions are likely, resolving the contradiction between power and capacity preservation.
3Reliability
If traditional battery management methods are used, then side reactions are minimized through rate limiting, but battery operation efficiency is reduced
Solution Approach 1:
The system implements feedback control using sensor data to continuously update the electrochemical model and adjust charging parameters in real-time, replacing open-loop rate limiting with closed-loop optimization that improves operational efficiency while protecting battery capacity.
Solution Approach 2:
The battery management system uses the battery's own electrochemical characteristics (modeled through differential algebraic equations) to determine optimal charging parameters, allowing the battery to effectively manage itself rather than being subject to conservative external limitations.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for efficient regulation of battery operations, minimizing side reactions and maintaining battery performance by accurately estimating states and parameters, thereby extending battery life and reducing charge times.
Implementation Method 1
Both electrodes contain active materials that react with lithium reversibly. During charging, there is generation of electrons at the positive electrode and consumption of an equal amount of electrons at the negative electrode. During discharging, opposite reactions occur.
Implementation Method 2
estimating, by the battery management system, at least one state of the at least one battery cell by applying the electrochemical-based battery model that applies differential algebraic equations to account for physical parameters of a chemical composition of the at least one battery cell
Data Source
AI summary
A method and system for managing a battery system. The method including receiving at least one measured characteristic of the battery over a pre-defined time horizon from the at least one sensor, receiving at least one estimated characteristic of the battery from a electrochemical-based battery model based on differential algebraic equations, determining a cost function of a Moving Horizon Estimation based on the at least one measured characteristic and the at least one estimated characteristic, updating the electrochemical-based battery model based on the cost function, estimating at least one state of the at least one battery cell by applying the electrochemical-based battery model, and regulating at least one of charging or discharging of the battery based on the estimation of the at least one state of the at least one battery cell.