Battery Internal Temperature Estimation for LiFePO4 Battery Based on Impedance Phase Shift under Operating Conditions

Determination of Internal Temperature Differences for Various Cylindrical Lithium-Ion Batteries Using a Pulse Resistance Approach

The temperature of lithium-ion batteries is crucial in terms of performance, aging, and safety. The internal temperature, which is complicated to measure with conventional temperature sensors, plays an important role here. For this reason, numerous methods exist in the literature for determining the internal cell temperature without sensors, which are usually based on electrochemical impedance spectroscopy. This study presents a method in the time domain, based on the pulse resistance, for determining the internal cell temperature by examining the temperature behavior for the cylindrical formats 18650, 21700, and 26650 in isothermal and transient temperature states for different states of charge (SOCs). A previously validated component-resolved 2D thermal model was used to analyze the location of the calculated temperature TR within the cell, which is still an unsolved question for pulse resistance-based temperature determination. The model comparison shows that TR is close to the average jelly roll temperature. The differences between surface temperature and TR depend on the SOC and cell format and range from 2.14K to 2.70K (18650), 3.07K to 3.85K (21700), and 4.74K to 5.45K (26650). The difference decreases for each cell format with increasing SOC and is linear dependent on the cell diameter.

Smart Core and Surface Temperature Estimation Techniques for Health-Conscious Lithium-Ion Battery Management Systems: A Model-to-Model Comparison

Estimation of core temperature is one of the crucial functionalities of the lithium-ion Battery Management System (BMS) towards providing effective thermal management, fault detection and operational safety. It is impractical to measure the core temperature of each cell using physical sensors, while at the same time implementing a complex core temperature estimation strategy in onboard low-cost BMS is also challenging due to high computational cost and the cost of implementation. Typically, a temperature estimation scheme consists of a heat generation model and a heat transfer model. Several researchers have already proposed ranges of thermal models with different levels of accuracy and complexity. Broadly, there are first-order and second-order heat resistor–capacitor-based thermal models of lithium-ion batteries (LIBs) for core and surface temperature estimation. This paper deals with a detailed comparative study between these two models using extensive laboratory test data and simulation study. The aim was to determine whether it is worth investing towards developing a second-order thermal model instead of a first-order model with respect to prediction accuracy considering the modeling complexity and experiments required. Both the thermal models along with the parameter estimation scheme were modeled and simulated in a MATLAB/Simulink environment. Models were validated using laboratory test data of a cylindrical 18,650 LIB cell. Further, a Kalman filter with appropriate process and measurement noise levels was used to estimate the core temperature in terms of measured surface and ambient temperatures. Results from the first-order model and second-order models were analyzed for comparison purposes.

Critical Review of Intelligent Battery Systems: Challenges, Implementation, and Potential for Electric Vehicles

This review provides an overview of new strategies to address the current challenges of automotive battery systems: Intelligent Battery Systems. They have the potential to make battery systems more performant and future-proof for coming generations of electric vehicles. The essential features of Intelligent Battery Systems are the accurate and robust determination of cell individual states and the ability to control the current of each cell by reconfiguration. They enable high-level functions like fault diagnostics, multi-objective balancing strategies, multilevel inverters, and hybrid energy storage systems. State of the art and recent advances in these topics are compiled and critically discussed in this article. A comprising, critical discussion of the implementation aspects of Intelligent Battery Systems complements the review. We touch on sensing, battery topologies and management, switching elements, communication architecture, and impact on the single-cell. This review contributes to transferring the best technologies from research to product development.

Building Safe Lithium-Ion Batteries for Electric Vehicles: A Review

Abstract

Lithium-ion batteries (LIBs), with relatively high energy density and power density, have been considered as a vital energy source in our daily life, especially in electric vehicles. However, energy density and safety related to thermal runaways are the main concerns for their further applications. In order to deeply understand the development of high energy density and safe LIBs, we comprehensively review the safety features of LIBs and the failure mechanisms of cathodes, anodes, separators and electrolyte. The corresponding solutions for designing safer components are systematically proposed. Additionally, the in situ or operando techniques, such as microscopy and spectrum analysis, the fiber Bragg grating sensor and the gas sensor, are summarized to monitor the internal conditions of LIBs in real time. The main purpose of this review is to provide some general guidelines for the design of safe and high energy density batteries from the views of both material and cell levels.

Graphic Abstract

Safety of lithium-ion batteries (LIBs) with high energy density becomes more and more important in the future for EVs development. The safety issues of the LIBs are complicated, related to both materials and the cell level. To ensure the safety of LIBs, in-depth understanding of the safety features, precise design of the battery materials and real-time monitoring/detection of the cells should be systematically considered. Here, we specifically summarize the safety features of the LIBs from the aspects of their voltage and temperature tolerance, the failure mechanism of the LIB materials and corresponding improved methods. We further review the in situ or operando techniques to real-time monitor the internal conditions of LIBs.