Dynamic Battery Charging Control via Real-Time State Modeling
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Solution Overview
Problem
Existing battery charging protocols are slow and lead to unnecessarily shortened battery lifetimes, failing to account for variations across batteries of the same manufacturing batch.
Innovation Solution
An apparatus and method for charging batteries that concurrently measures voltage and current, using a processor to update a dynamic representation of battery cell dynamics and apply an optimized charging current based on a charging profile, tracking total charge and temperature, and employing nonlinear system identification to derive a set of internal state variables and model parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional charging protocols are used, then charging process is simple and reliable, but charging time is long and battery lifetime is unnecessarily shortened
Solution Approach 1:
The charging protocol dynamically adjusts charging parameters (current, voltage, power) in real-time based on measured battery state variables (temperature, voltage, current, charge amount) and model predictions, transitioning from static conventional charging to adaptive dynamic charging that optimizes charging speed while protecting battery life
Solution Approach 2:
The system continuously measures battery parameters (voltage, current, temperature) during charging, compares actual values with model predictions, and adjusts charging parameters accordingly through feedback control, enabling real-time optimization of charging performance
Solution Approach 3:
The charging protocol changes operational parameters (charging current, voltage, power levels) based on battery state and model predictions, allowing the system to optimize charging speed at different stages of the charging process while preventing harmful effects
2Reliability
If manufacturer-specified charging procedures are followed, then charging process is safe and reliable, but charging time is extended and battery longevity is reduced
Solution Approach 1:
The system performs preliminary identification of battery characteristics before charging begins, establishing a customized model that predicts safe operating boundaries and optimal charging parameters specific to each battery, enabling faster yet safe charging from the start
Solution Approach 2:
The charging protocol adjusts electrical parameters (current, voltage, power) based on real-time battery state and model predictions, allowing higher charging rates within safety boundaries that are dynamically determined rather than using fixed conservative limits
3Productivity
If uniform charging protocol is applied to all batteries, then charging process is simple to implement, but variations across batteries of the same manufacturing batch are not accounted for
Solution Approach 1:
The system customizes charging parameters and model predictions for each individual battery based on its specific characteristics (measured during identification), treating each battery locally rather than applying a uniform protocol, enabling optimized charging speed for each unit
Solution Approach 2:
Each battery effectively serves itself by providing its own characteristic data during identification, which the system uses to build a customized model and determine optimal charging parameters specific to that battery, eliminating the need for complex external classification systems
Data Source
AI summary
An apparatus and methods for ultra-fast charging one or more batteries, including, for example, lithium ion batteries. A charging current is determined by optimization of a model based on functions of a set of internal state variables associated with a battery, and a set of model parameters or nonparametric data characterizing the battery. Instantaneous internal state variables are determined, and an optimized charging current is applied to the battery subject to a set of battery-specific constraints. Internal state variables are updated recursively based on behavior of the battery under charge as well as the behavior, stored in a database, or acquired via a network, of cognate batteries.