Battery Control Unit for Real-Time SOC Estimation Using Kalman Filtering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for determining the state of charge (SOC) of rechargeable batteries in vehicles are inaccurate and cannot provide real-time measurements due to reliance on pre-set values and sensitive measurement errors, especially when batteries are in constant charge and discharge cycles during operation.
Innovation Solution
A battery control unit using a 1-RC equivalent circuit model and a Kalman filter to estimate open circuit voltage (OCV) and other parameters in real-time, allowing for accurate SOC estimation without requiring the battery to sit idle, and incorporating multiple battery chemistries for improved performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods using pre-set values are used to determine SOC, then the measurement process is simple, but the measurement precision is poor and real-time estimation is not achieved
Solution Approach 1:
The patent introduces an intermediary estimation process that uses measurable parameters (voltage, current, temperature) as mediators to infer the difficult-to-measure SOC and SOH parameters. The system uses voltage as an intermediary to estimate OCV, which then serves as a basis for SOC estimation, avoiding direct measurement of SOC while improving accuracy through the intermediary estimation chain.
Solution Approach 2:
The patent replaces traditional mechanical/electrical measurement systems with a computational estimation system. Instead of using complex hardware to directly measure SOC, the system substitutes a software-based parameter estimation algorithm that processes readily available electrical parameters (voltage, current, temperature) to compute SOC and SOH, reducing hardware complexity while improving measurement precision.
2Measurement precision
If the battery sits idle for extended rest periods to achieve accurate measurements, then measurement precision improves, but productivity and real-time monitoring capability deteriorate
Solution Approach 1:
The patent makes the estimation system dynamic by continuously updating SOC and SOH parameters in real-time as the battery operates. The system adapts to changing battery conditions during charge/discharge cycles, adjusting estimates based on current voltage, current, and temperature measurements without requiring the battery to remain static or idle, thus maintaining both precision and productivity.
Solution Approach 2:
The patent enables continuous parameter estimation during battery operation. The system continuously processes voltage, current, and temperature data to update SOC and SOH estimates in real-time, eliminating the need to interrupt battery usage for measurement. This continuous estimation approach maintains useful action (battery operation) while achieving accurate parameter monitoring.
3Reliability
If traditional SOC determination methods are used, then device complexity is low, but reliability of SOC indication deteriorates due to sensitivity to measurement errors
Solution Approach 1:
The patent implements feedback mechanisms where the estimated SOC and SOH parameters are continuously refined based on comparison with actual measurements. The system uses feedback from voltage, current, and temperature measurements to correct and improve estimation accuracy, making the SOC indication more reliable. The feedback loop compensates for measurement errors by adjusting estimates based on the relationship between multiple parameters.
4Adaptability or versatility
If pre-set values are used for SOC determination, then ease of operation is high, but measurement precision and adaptability to different battery chemistries worsen
Solution Approach 1:
The patent creates a universal parameter estimation system that can handle multiple battery chemistries (Li-ion, LiFePO4, NiMH, etc.) through a single algorithmic framework. The system uses universal relationships between voltage, current, temperature, and battery state that apply across different chemistries, making the system adaptable and versatile without requiring chemistry-specific hardware or complex operation procedures.
Data Source
Figure 1~2
Figure 3~4
Figure 5
AI summary
A battery system includes a battery that couples to an electrical system. The battery system also includes a battery control module that electrically couples to the battery. The battery control module monitors at least one monitored parameter of the battery, and the battery control module recursively calculates at least one calculated parameter of the battery based on at least an equivalent circuit model, the at least one monitored parameter, and a Kalman filter.