Battery State Excitation for Dynamic Internal Model Control
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Solution Overview
Problem
Existing automated control systems for batteries face challenges in managing uncertainty and effectively controlling battery operations due to unknown internal states and changing conditions, as they often rely on static models and optimization techniques that do not account for real-time feedback and dynamic changes.
Innovation Solution
The implementation of inference automaton tomography techniques, which involve actively exciting battery systems with small variations to measure responses and generate real-time models of internal states, allowing for dynamic control and optimization of battery operations without altering the system's behavior significantly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If automated control systems use static models and optimization techniques, then control simplicity is maintained, but accuracy in managing uncertainty and detecting anomalies deteriorates
Solution Approach 1:
The patent transforms static control models into dynamic models that continuously adapt to changing battery conditions. The system updates model parameters in real-time based on observed battery behavior, allowing the control system to accurately track internal states such as temperature and charge level even as operating conditions change. This dynamic adaptation resolves the contradiction by maintaining model accuracy without requiring overly complex static pre-computation.
Solution Approach 2:
The patent implements feedback mechanisms where the control system continuously monitors battery responses to control actions and uses this information to update its internal models. By comparing predicted behavior from static models with actual observed behavior, the system identifies discrepancies and adjusts model parameters accordingly. This feedback loop enables accurate uncertainty management and anomaly detection while keeping the overall control architecture relatively simple.
2Measurement precision
If excitation signals are applied to measure internal battery states, then measurement precision improves, but the system behavior is altered
Solution Approach 1:
The patent applies excitation signals selectively at specific locations and times within the battery system rather than continuously or uniformly. By applying small, localized perturbations only when needed for measurement purposes and using different excitation strategies for different battery states, the system obtains precise internal state measurements while minimizing disruption to overall battery behavior and operation.
Solution Approach 2:
The patent uses small-amplitude excitation signals that are sufficient for measurement purposes but too weak to significantly alter battery behavior. By applying partial action (small perturbations rather than full-scale testing), the system achieves the necessary measurement precision to detect internal states and anomalies while maintaining normal battery operation and stability during excitation events.
Data Source
AI summary
Techniques are described for implementing automated control systems for target battery systems based at least in part on battery state information gathered from active excitation of the batteries, such as to maximize battery life while performing other battery power use activities. The excitation of a target battery system may occur while it is in use, by repeatedly introducing small defined variations as input to the battery system while the battery system is otherwise used to supply or receive electricity. Corresponding small variations in output of the battery system from the excitation activities are then measured by hardware sensors, aggregated and analyzed to generate a current model of the internal state of the one or more batteries, and then used to assist in controlling further operations of the battery system, including in some cases to update a previously existing model of the battery system.