A Temperature-Dependent State of Charge Estimation Method Including Hysteresis for Lithium-Ion Batteries in Hybrid Electric Vehicles

Abstract

Currently, lithium-ion batteries are mainly used as central power components in electric vehicles. Usually, accurate battery cell modeling and state of charge estimation are required in order to effectively use the lithium-ion batteries in electrified vehicles. For an elaborate battery cell modeling on a wide temperature range, we select a temperature-dependent battery cell modeling approach, which relies on one resistance plus second-order resistance-capacitance equivalent circuit model. In order to corporate some temperature effects into the modeling, we derive the sixth-order polynomial functions using the curve fitting algorithm. The functions contribute to the accurate battery cell modeling on the wide temperature range. For a practical usage of the functions in real-time embedded systems, we propose an offset-based lookup table technique. In addition, we propose a novel hysteresis voltage unit model for more accurate parameter estimation of hysteresis voltages. This also leads to more accurate battery cell modeling. Based on the battery cell modeling, we propose a temperature-dependent estimation method for state of charge. This approach exploits the extended Kalman filter, which is suitable for nonlinear characteristics such as the hysteresis effect. Experimental evaluation exhibits that the proposed estimation method outperforms the conventional approaches in the wide temperature range.

Fuzzy adaptive singular value decomposition cubature Kalman filtering algorithm for lithium‐ion battery state‐of‐charge estimation

“…Common lithium-ion battery equivalent models include Thevenin equivalent model, PNGV model, and second-order RC model. [33][34][35][36][37][38] Taking into account the requirements of battery simulation accuracy and the principle of minimizing the amount of calculation, a secondorder RC equivalent model is selected to perform equivalent simulations of lithium-ion batteries. For the internal resistance of the battery that is different during charging and discharging, the internal resistance of the battery for charging and discharging is calculated separately to form a double internal resistance second-order RC model.…”

“…A reasonable battery equivalent model is the basis for accurate SOC estimation. Common lithium‐ion battery equivalent models include Thevenin equivalent model, PNGV model, and second‐order RC model 33–38 . Taking into account the requirements of battery simulation accuracy and the principle of minimizing the amount of calculation, a second‐order RC equivalent model is selected to perform equivalent simulations of lithium‐ion batteries.…”

Supporting the Transition Towards Electromobility in the Construction and Mining Sector: Optimization Framework and Demonstration on an Electrical Hauler

“…The control inputs 𝑢 ̅ comprised of propelling and braking force at the motor shaft. Contextual variables mainly influenced the disciplinary analysis, such as ambient temperature affecting the battery (Choi and Chang, 2020) or rolling resistance and air density (Wang et al, 2018), while elevation profile affecting the regenerative capability and so on. Also, the operational scenario was assumed to consist of a wheel loader having a 5-ton capacity.…”

Parameter and State of Charge Estimation Simultaneously for Lithium‐Ion Battery Based on Improved Open Circuit Voltage Estimation Method

“…Another method of addressing this issue is described as follows: [ 52,53 ] the current is constant in the charging and discharging process of the cell. Therefore, the instantaneous voltage change at the beginning or end of charging (or discharging) can be simply regarded as the voltage change caused by Ohmic resistance.…”