Battery Module Temperature Estimation for Sparse Sensor BMS
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Solution Overview
Problem
Conventional battery management systems face challenges in accurately detecting the highest and lowest temperatures in battery modules due to limited temperature sensors, leading to inefficient charging control and thermal management.
Innovation Solution
A method and device for determining a temperature estimating model that calculates parameter sets based on selected models, verifies these sets using preliminary and re-verification profiles, and adjusts error thresholds to accurately estimate the highest and lowest temperatures, improving thermal management in battery modules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only one or two temperature sensors are installed in the battery module due to manufacturing limits and cost, then the device complexity and manufacturing cost are reduced, but the measurement precision of highest and lowest temperatures deteriorates
Solution Approach 1:
The patent introduces a temperature estimation model as an intermediary that uses data from limited temperature sensors combined with battery operating parameters (current, voltage, time) to calculate and estimate temperatures at multiple battery cell locations. This mediator enables accurate temperature measurement without requiring physical sensors at every location, thus resolving the contradiction between measurement precision and device complexity.
Solution Approach 2:
The patent creates virtual temperature copies by using the temperature estimation model to generate temperature values for battery cells where physical sensors are not installed. The model replicates the temperature measurement function through mathematical calculations based on heat transfer equations, allowing the system to obtain temperature data for all cells as if sensors were present at each location.
2Measurement precision
If multiple temperature sensors are installed to accurately detect highest and lowest temperatures, then the measurement precision improves, but the device complexity and manufacturing cost increase
Solution Approach 1:
The temperature estimation model serves as an intermediary computational system that processes data from minimal physical sensors combined with battery operating parameters to derive temperature information for all battery cells. This approach eliminates the need for multiple physical sensors while maintaining accurate temperature detection capability.
Solution Approach 2:
The patent replaces the mechanical approach of installing multiple physical temperature sensors with a computational model based on heat transfer equations. The model uses mathematical calculations involving thermal conductivity, heat capacity, and battery operating conditions to substitute for physical sensing infrastructure, thereby reducing device complexity while maintaining measurement precision.
3Device complexity
If a simple temperature estimation model is used, then the device complexity is reduced, but the measurement precision of temperature estimation deteriorates
Solution Approach 1:
The patent employs a temperature estimation model that dynamically adjusts calculation parameters based on battery operating conditions (current, voltage, time, ambient temperature). The model changes its computational parameters adaptively to reflect real-time battery state, maintaining high estimation precision without requiring overly complex model structures. This parameter adaptation allows the model to achieve accurate results across varying operating conditions.
Solution Approach 2:
The temperature estimation model incorporates dynamic characteristics by continuously updating temperature estimates based on real-time battery operating data and thermal history. The model adapts its calculations to reflect changing battery conditions, enabling accurate temperature estimation throughout charge/discharge cycles without requiring static or overly complex model structures.
Data Source
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AI summary
A method for determining a temperature estimating model for estimating a temperature in a battery module includes: estimating temperatures by substituting input data of a preliminary verification profile with models based on all the respective parameter sets; calculating a first error caused by a difference between measured temperatures of the preliminary verification profile and the estimated temperatures; comparing whether respective first errors for all the respective parameter sets are less than a first threshold value; extracting a parameter set corresponding to the first error that is less than the first threshold value from among the first errors as a first parameter set; calculating a maximum error that is the biggest error from among the errors between the temperatures estimated according to the input data changeable in a time-series way of the preliminary verification profile and measured temperatures of the preliminary verification profile by using a model based on the first parameter set; extracting a second parameter set based on a result of adding a product of the maximum error that is less than the second threshold value according to the comparison result and a corresponding weight value and a product of a first error corresponding to the first parameter set from among the first errors and a corresponding weight value; estimating temperatures according to input data of a reverification profile to the second parameter set; calculating a second error according to a difference between measured temperatures of the reverification profile and the estimated temperatures; and determining the model based on the second parameter set to be a temperature estimating model when the second error is less than a third threshold value.