Constrained generalized predictive control of battery charging process based on a coupled thermoelectric model

Abstract

Battery temperature is a primary factor affecting the battery performance. Suitable battery temperature control, in particular internal temperature control can not only guarantee the battery operation safety but also improve its efficiency. This is however challenging as existing controller designs for battery charging rarely have a mechanism to incorporate such information. This paper proposes a novel battery charging control strategy which applies the constrained generalized predictive control (GPC) to charge a LiFePO4 battery based on a newly developed coupled thermoelectric model. The control target primarily aims to maintain the battery internal temperature within a desirable range while delivering fast charging. To achieve this, the coupled thermoelectric model is firstly introduced to capture the battery behaviours in particular SOC and internal temperature which are not directly measurable. Then a controlled auto-regressive integrated moving average (CARIMA) model, whose structure is optimized by a fast recursive algorithm and the parameters are identified by the recursive least squares algorithm, is developed as an online self-tuning predictive model for a GPC controller. Then the constrained generalized predictive controller is developed to manipulate the charging current. Experiment results confirm the effectiveness of the proposed control strategy. Further, the best region of the heat dissipation rate and proper internal temperature set-points are investigated and analysed.

A brief review on key technologies in the battery management system of electric vehicles

“…However, often a large quantity of information needs to be stored by using DP, which leads to large computation cost especially in high dimension charging problems. The MPC-based charging approaches also need to design a suitable battery model firstly [134][135][136]. Then the charging behaviours such as current, voltage, and even temperature can be predicted directly by the designed electric model or thermal model.…”

A novel multiobjective charging optimization method of power lithium‐ion batteries based on charging time and temperature rise

“…Hu Xiaosong presented a dual‐objective charging optimization strategy for LiNMC and LiFePO 4 to balance charging time and loss . Li Kang proposed a constrained generalized predictive control method to maintain the battery internal temperature within a desirable range . The method is verified to be effective to reduce the internal temperature, but the close‐loop control is too complex to be applied in practice, and charging takes a long time.…”

“…9 Li Kang proposed a constrained generalized predictive control method to maintain the battery internal temperature within a desirable range. 10 The method is verified to be effective to reduce the internal temperature, but the close-loop control is too complex to be applied in practice, and charging takes a long time. Zhang Caiping developed a polarization-based optimization strategy to enhance charging speed and reduce temperature rise with genetic algorithm (GA) method.…”

Numerical Analysis of the Cooling Performance in a 7.2 kW Integrated Bidirectional OBC/LDC Module

“…In addition, as cooling performance has become an important consideration in circuit improvement, experimental methods of evaluating the cooling performance of heating elements are also being researched [14]. Note that such studies typically employ experimental methods instead of the numerical methods commonly used in battery pack design [15].Recently, the Buck Converter of the two-way charging system has been proposed as an optimization control method considering the State of Charging (SOC) [16][17][18][19][20] and the State of Healthy (SOH) [21][22][23], and the research is being actively conducted. Among the SOC methods, the CC-CV (Constant Current/Constant Voltage) method, which is the simplest basic model and is controlled according to the determined voltage and current [16], and the CVCC-CV (Constant Voltage/Constant Current/Constant Voltage) and MCC-CV (Multi-Stage Constant Current/Constant Voltage) have been proposed for fast charging and securing cycle stability [17,18].…”

“…In addition, under high temperature conditions, the battery surface may exceed the allowable temperature depending on the state of charge and discharge, resulting in a negative performance such as battery life cycle and charging acceptance. The method considering SOH has been proposed as a method for checking battery life and water solubility to improve performance degradation problems and stability problems due to overheating, and research for checking the effects of temperature, energy efficiency, and battery aging has been carried out [22,23].In previous studies, efforts have been made to improve circuit efficiency and improve cooling performance. However, most of the previous studies are designed considering only specific conditions or conditions for main modes.…”