Modular Battery Temperature Estimation Using EIS and Kalman Tracking
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Solution Overview
Problem
Current methods for monitoring internal battery temperature in lithium-ion batteries, especially in electric vehicles, are inadequate due to delays in heat conductivity and the cost and complexity of thermocouple networks, leading to inaccurate temperature readings and potential premature battery failure.
Innovation Solution
The use of electrochemical impedance spectroscopy (EIS) combined with Kalman Filter-based techniques and lumped thermal models to estimate internal battery temperature, allowing for accurate tracking of temperature gradients and interpolation of low-sample-rate measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If thermocouple networks are used to monitor internal battery temperature, then temperature measurement capability is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent extracts the temperature sensing function from physical thermocouple sensors and implements it through electrical impedance measurements. By measuring the battery's impedance at different frequencies, the system can estimate internal temperature without requiring physical temperature sensors to be inserted into the battery, thereby reducing device complexity while maintaining measurement capability.
Solution Approach 2:
The patent introduces electrical impedance as an intermediary parameter to indirectly measure internal battery temperature. Instead of directly measuring temperature with thermocouples, the system measures impedance changes that correlate with temperature variations, using impedance as a mediator between the measurement system and the temperature parameter.
2Ease of manufacture
If surface-mounted thermal sensors are used, then installation simplicity is improved, but measurement accuracy deteriorates due to heat conductivity delays
Solution Approach 1:
The patent replaces the mechanical/physical thermocouple sensing system with an electrical measurement system. Instead of using physical sensors that rely on thermal conduction to detect temperature, the system uses electrical impedance spectroscopy to infer temperature, eliminating the need for thermal conduction and its associated delays.
Solution Approach 2:
The patent uses electrical impedance as an intermediary that responds directly to temperature changes without the thermal conduction delay problem. Impedance measurements provide direct information about the battery's internal state, including temperature, without requiring heat to physically travel from the internal to the surface where sensors are mounted.
3Device complexity
If multiple battery packs are monitored with a single tracker, then device complexity is reduced, but measurement precision and response time deteriorate
Solution Approach 1:
The patent segments the temperature estimation function into modular, battery-specific models. Each battery pack has its own thermal model parameters that can be independently learned and updated, allowing the system to maintain high measurement precision for each individual battery while using a standardized tracking architecture that keeps overall device complexity manageable.
Solution Approach 2:
The patent implements local quality by allowing each battery pack to have its own customized thermal model parameters adapted to its specific characteristics. This enables precise, localized temperature estimation for each battery while using a common overall system architecture, balancing individual accuracy with system-wide simplicity.
4Productivity
If fast charging is performed, then productivity is improved, but internal temperature increases causing thermal safety issues
Solution Approach 1:
The patent implements feedback by continuously monitoring battery impedance changes during charging and using this information to estimate internal temperature in real-time. This feedback mechanism allows the charging system to adjust charging parameters based on the estimated internal temperature, enabling fast charging while maintaining thermal safety through dynamic control adjustments.
Solution Approach 2:
The patent applies preliminary action by learning and storing thermal model parameters before fast charging operations begin. These pre-learned parameters enable the system to quickly and accurately estimate temperature during fast charging events, allowing for proactive thermal management adjustments before dangerous temperature levels are reached.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables precise estimation of internal battery temperature, improving battery performance, extending lifespan, and enhancing thermal safety in electric vehicles by reducing the need for surface-mounted thermal sensors and simplifying model parameter learning.
Implementation Method 1
The use of electrochemical impedance spectroscopy (EIS) combined with Kalman Filter-based techniques and lumped thermal models to estimate internal battery temperature
Implementation Method 2
lumped thermal models to estimate internal battery temperature, allowing for accurate tracking of temperature gradients
Data Source
AI summary
Modular temperature tracking techniques can be used to estimate internal battery temperatures of battery packs. For example, an electric vehicle can contain a plurality of battery packs. Battery packs of electric vehicles can be composed of several modules each of which may contain multiple batteries in series. A plurality of independent temperature trackers for each cell can be used instead of a single large estimator.