Dynamic Battery Model Parameter Update
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Solution Overview
Problem
Existing battery state estimation technologies face challenges in accurately estimating battery health and capacity over time, especially when insufficient reference data is available, leading to inaccurate predictions and prolonged development times for new battery materials or configurations.
Innovation Solution
A processor-implemented method that determines the validity of a battery model by comparing estimated state information with predefined ranges, requesting updates from an external server when the model is invalid, and updating the model using new parameters to maintain accurate estimation, even with changing battery conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed battery model with predetermined parameters is used for state estimation, then the device complexity is reduced and ease of operation is improved, but the measurement precision deteriorates when battery conditions change over time
Solution Approach 1:
The battery model transitions from a static fixed-parameter model to a dynamic model that automatically adapts its parameters based on battery state. The system continuously monitors battery information and updates model parameters in response to changing battery conditions, ensuring the model remains accurate throughout the battery lifecycle without requiring manual intervention.
Solution Approach 2:
The system implements a feedback mechanism where the estimated battery state is continuously compared against actual battery information. When discrepancies are detected or when battery conditions change, the system automatically requests updated parameters from external providers or adjusts parameters based on monitored data, creating a closed-loop system that maintains estimation accuracy.
2Measurement precision
If battery model parameters are manually updated frequently to maintain accuracy, then the measurement precision is improved, but the loss of time increases due to manual intervention and validation
Solution Approach 1:
The battery management system performs self-updating of model parameters by automatically monitoring battery state and triggering parameter updates when necessary. The system validates updated parameters against predetermined criteria and can autonomously request new parameters from external providers, eliminating the need for manual model validation and reducing time loss.
Solution Approach 2:
The system pre-establishes validity criteria and update triggers based on predetermined minimum levels and estimation ranges. By preparing validation rules in advance and automatically comparing updated parameters against these pre-set criteria, the system streamlines the update process and reduces the time required for model validation.
3Adaptability or versatility
If the battery model estimation range is expanded to cover all possible battery states, then the adaptability is improved, but the measurement precision deteriorates due to insufficient reference data for all conditions
Solution Approach 1:
The battery model estimation range is divided into multiple segments or sub-ranges, each with its own optimized parameters and validity criteria. Instead of using a single broad model that compromises precision, the system segments the estimation space and applies appropriate parameters for each segment, maintaining high accuracy across the full range of battery conditions.
Solution Approach 2:
Different parameter sets and model configurations are applied to different regions of the battery state space based on local conditions. The system selects or updates parameters specific to the current battery state segment, ensuring that each local region has optimized parameters tailored to its characteristics rather than using a generic global parameter set.
4Reliability
If continuous monitoring and model updating is implemented, then the reliability is improved, but the use of energy increases due to continuous processing and communication
Solution Approach 1:
Instead of continuous monitoring and updating, the system implements periodic model validation and parameter updates triggered by specific events or time intervals. The system monitors battery state continuously but only initiates model updates when predetermined conditions are met, such as when the battery reaches certain state thresholds or when validity criteria indicate parameter changes are needed, reducing energy consumption while maintaining reliability.
Data Source
AI summary
Provided is a battery state estimation apparatus and method that determine a validity of a battery model, which is dependent on a parameter, based on state information of a battery that is estimated from battery information of the battery, transmit an update request for the battery model to an external battery model provider in response to a result of the determining indicating that the battery model is invalid, receive another parameter in response to the update request, and update the battery model based on the other parameter.