Traction Battery Charge Control for Accurate SOC Estimation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for monitoring the operating characteristics of traction batteries in electrified vehicles are inadequate during charging, particularly when using AC or DC charging currents, leading to inaccurate state-of-charge (SOC) estimation and inefficient battery management.
Innovation Solution
Implementing an active charge control strategy that varies the charging current based on the type of charging current (AC or DC) to provide a diverse set of measurements for the Kalman filter, allowing accurate estimation of battery parameters and states during charging, using a traction battery controller with a battery energy control module (BECM) to manage the charging process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If active charge control is implemented to vary charging current for accurate SOC estimation, then measurement precision is improved, but charging time increases
Solution Approach 1:
The charging current is dynamically varied during the charging process to excite the battery system and generate diverse voltage measurements. The controller adjusts the charging current profile adaptively based on battery state, enabling accurate SOC estimation through Kalman filter algorithms while minimizing impact on overall charging time.
Solution Approach 2:
The charging current parameters are changed and modulated during charging to create measurable voltage responses. By varying current magnitude and timing, the system generates sufficient measurement diversity for accurate parameter estimation without significantly extending the charging duration.
2Measurement precision
If charging current is varied for multiple instants to improve SOC estimation, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system employs feedback control where the controller continuously monitors battery voltage and current, processes measurements through Kalman filter algorithms, and adjusts the charging current accordingly. This closed-loop feedback mechanism enables accurate SOC estimation while managing control complexity through systematic decision-making based on real-time battery state.
Data Source
AI summary
A method includes varying a charging current, from a charge station for use in charging a battery, depending on a type of the charging current. The battery may be a traction battery of an electrified vehicle. The method further includes measuring a voltage of the battery as the charging current is being varied, driving an estimator, that utilizes voltage feedback based on a model of the battery to provide parameter/state estimations of the battery, with the voltage to output a state-of-charge (SOC) of the battery, detecting an operating characteristic of the battery using the SOC, and controlling the battery according to the operating characteristic.