Battery Surface Temperature Mapping With Sparse Sensor Inputs
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Solution Overview
Problem
Existing battery monitoring technologies lack the ability to accurately track maximum and minimum surface temperatures of individual cells within a battery pack without extensive use of thermocouples, and are constrained by memory and computational limitations, which can lead to safety risks and diminished battery life.
Innovation Solution
Combining model-based temperature estimates with condensed information, such as physics-based models and data-driven representations, to generate high-resolution surface temperature maps using techniques like multivariable polynomial regression, lumped Kalman filters, joint low-rank decomposition, and subspace-based super-resolution, without relying on dense sensor networks or excessive computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dense sensor networks (extensive thermocouples) are used to accurately measure surface temperatures, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent introduces a thermal model as an intermediary between the battery cells and the measurement system. This model uses a small number of temperature sensors combined with thermal diffusion equations to estimate temperatures throughout the battery pack, eliminating the need for dense sensor networks while maintaining measurement accuracy
Solution Approach 2:
The patent creates a virtual copy of the battery thermal behavior through mathematical modeling. By simulating the thermal dynamics and using this virtual model to interpret limited sensor data, the system achieves comprehensive temperature monitoring without physical sensors at every location
2Reliability
If high-resolution temperature mapping is implemented to identify localized hot spots, then safety and battery life are improved, but computational resources and memory requirements increase
Solution Approach 1:
The patent divides the battery pack into discrete thermal zones or segments, each governed by simplified thermal equations. This segmentation allows the system to track temperature distribution across the entire pack using manageable computational units rather than processing continuous complex thermal fields
Solution Approach 2:
The patent transforms the thermal monitoring problem from tracking absolute temperatures at numerous points to estimating a smaller set of critical thermal parameters (such as average temperatures per zone or key gradient parameters). This parameter reduction maintains safety monitoring capability while significantly reducing computational burden
3Device complexity
If model-based estimation techniques are used to reduce sensor requirements, then device complexity is reduced, but measurement precision may deteriorate without proper calibration
Solution Approach 1:
The patent implements feedback mechanisms where the thermal model continuously compares its estimates with actual sensor measurements and adjusts its parameters accordingly. This feedback loop ensures that the model remains calibrated and accurate while using minimal sensors, resolving the trade-off between model simplicity and measurement precision
Data Source
AI summary
Systems and methods for estimating battery surface temperatures comprise generating a core temperature estimate for the battery based on a battery model. A set of lumped temperature states may be generated based on the core temperature, the set of lumped temperature states comprising temperature estimates for different regions of the battery. Additional condensed information may be retrieved relating to the battery. A surface temperature map may be generated for the battery based on the set of lumped temperature states and the additional condensed information using a mapping function.