This book focuses on the thermal management technology of lithium-ion batteries for vehicles. It introduces the charging and discharging temperature characteristics of lithium-ion batteries for vehicles, the method for modeling heat generation of lithium-ion batteries, experimental research and simulation on air-cooled and liquid-cooled heat dissipation of lithium-ion batteries, lithium-ion battery heating method based on PTC and wide-line metal film, self-heating using sinusoidal alternating current. This book is mainly for practitioners in the new energy vehicle industry, and it is suitable for reading and reference by researchers and engineering technicians in related fields such as new energy vehicles, thermal management and batteries. It can also be used as a reference book for undergraduates and graduate students in energy and power, electric vehicles, batteries and other related majors.
This report presents the electrothermal analysis and testing of lithium ion battery performance. The objectives of this report are to: (1) develop an electrothermal process/model for predicting thermal performance of real battery cells and modules; and (2) use the electrothermal model to evaluate various designs to improve battery thermal performance.
This report presents the electrothermal analysis and testing of lithium ion battery performance. The objectives of this report are to: (1) develop an electrothermal process/model for predicting thermal performance of real battery cells and modules; and (2) use the electrothermal model to evaluate various designs to improve battery thermal performance.
This research presents a method for efficiently and reproducibly comparing diverse battery thermal management concepts in an early stage of development to assist in battery system design. The basis of this method is a hardware-based thermal simulation model of a prismatic Lithium-Ion battery, called the Smart Battery Cell (SBC). By eliminating the active chemistry, enhanced reproducibility of the experimental boundary conditions and increased efficiency of the experimental trials are realized. Additionally, safety risks associated with Lithium-Ion cells are eliminated, making the use of the SBC possible with thermal management systems in an early state of developed and without costly safety infrastructure. The integration of thermocouples leaves the thermal contact surface undisturbed, allowing the SBC to be integrated into diverse thermal management systems.
Thermal Management of Batteries presents a comprehensive examination of the various conventional and emerging technologies used for thermal management of batteries and electronics. With an emphasis on advanced nanofluids, the book provides step-by-step guidance on advanced techniques at the component and system level for both active and passive technologyStarting with an overview of the fundamentals, each chapter quickly builds into a comprehensive treatment of up-to-date technologies. The first part of the book discusses advanced battery technologies, while the second part addresses the design and performance optimization of battery thermal management systems. Power density and fast charging mechanisms of batteries are considered, as are role of thermal management systems on performance enhancement. The book discusses the design selection of various thermal management systems, parameters selection for different configurations, the operating conditions for different battery types, the setups used for experimentation and instrumentation, and the operation of thermal management systems. Advanced techniques such as heat pipes, phase change materials, nanofluids, novel heat sinks, and two phase flow loops are examined in detail.Presenting the fundamentals through to the latest developments alongside step-by-step guidance, mathematical models, schematic diagrams, and experimental data, Thermal Management of Batteries is an invaluable and comprehensive reference for graduates, researchers, and practicing engineers working in the field of battery thermal management, and offers valuable solutions to key thermal management problems that will be of interest to anyone working on energy and thermal heat systems. Critically examines the components of batteries systems and their thermal energy generation Analyzes system scale integration of battery components with optimization and better design impact Explores the modeling aspects and applications of nanofluid technology and PCMs, as well as the utilization of machine learning techniques Provides step-by-step guidance on techniques in each chapter that are supported by mathematical models, schematic diagrams, and experimental data
Abstract: Electrical storage technologies (i.e., batteries) play a ubiquitous role in all facets of modern technologies for applications ranging from very small to very large scale, both stationary and mobile. In the past decade, Li-ion batteries are quickly emerging as the preferred electrical energy storage technology due to the intrinsic power and energy storage density compared to older battery chemistries. All electrochemical batteries are strongly linked to their thermal state: on one hand, their electrical characteristics are strongly dependent on temperature and, on the other hand, their thermal state is a result of both their environmental temperature, but also their electrical usage due to internal heat generation. Furthermore, their life (and potentially safety) is also strongly affected by their thermal state. Li-ion batteries, due to their high electrical power capability and density tend to be used aggressively in many applications, rendering the thermal issues more acute. Finally, Li-ion battery packs (like all packs) are made of many cells interconnected in various series/parallel arrangements in tightly confined spaces. Hence, thermal management solutions need to be implemented for two primary reasons: rejecting the heat generated inside the pack to the environment to avoid high (or unsafe) temperatures leading to premature (or catastrophic) failure and providing a good thermal uniformity among all the cells so that their electrical performance (and aging) in well matched in a pack. This thesis focuses on the thermal modeling of Li-ion packs and the development of passive thermal management solutions for such packs. The thesis first provides an extensive review of the current literature on Li-ion batteries electrical and thermal modeling and current approaches for thermal management solutions of Li-ion packs. This study then focuses on a particular current application using a small Li-ion pack, namely a contractor-grade 36v cordless drill. This particular application was chosen as it encapsulates many of the features of larger automotive packs and represent and leads to an aggressive usage pattern where battery life is always an issue. This pack was experimentally studied to establish typical usage patterns and to measure the thermal and electrical state of the stock pack during such usage. The study then developed and validated a FEM computational pack model in the stock configuration. This experimentally validated models was then used as a proxy to reality to numerically investigate multiple possible configurations of passive thermal management solutions using a high thermal conductivity, Graphite-based heat spreading material to both reduce temperature non-uniformities within the pack and decrease of overall pack temperature (better heat rejection) during aggressive use. Finally, a preliminary experimental validation of one of the promising configurations of heat spreaders was investigated. The work described in this thesis clearly demonstrates that passive heat spreading technology can be very beneficial to reduce thermal stress on batteries and lead to more thermally homogenous packs. Furthermore, this study demonstrated that the investigation of such solutions can be performed with validated thermal FEM models to speed up the development of actual solution and reduce experimental prototype building. Future work will include more configurations, but also experimental investigation of battery life for both thermally managed and unmanaged packs under similar (aggressive) usage patterns. Finally, the conclusions from this study conducted on a cordless power tool are probably equally applicable to large automotive battery packs where life and costs are critical.
The use of energy is required to make human life comfortable and energy storage is as critical as energy supply. Among the different systems that can be utilized for the storage of energy, batteries are one of the most common and portable ones. Moreover, there has been a growing demand for lithium-ion Batteries (LIBs) over the last few decades due to their high performance within cycle life, energy and power density. One of the major concerns of LIBs is the safe operations and the prevention of a battery causing fire or explosion, which is known as “thermal runaway”. In this study, two different ways to prevent catastrophic thermal runaway will be investigated. One way is to develop a thermoelectrochemical model to predict thermal behavior of a battery. In this case, the investigation of thermodynamic quantities such as entropy change is essential as it is directly related to temperature prediction of the system. In this study, the typical methodologies to measure the entropy change were investigated. It has been shown that side reactions of cells can interfere with obtaining accurate measurement results of entropy changes. Moreover, a physics-based electrochemical model was introduced for the new methodology to measure entropy change which is known as “the frequency-domain method”. Differing from the initial frequency domain method, the change of entropy is physically coupled to the internal state changes of batteries. This method reduces the time of the entropy change measurement by scale of 100, in comparison to the traditional methods. Solid-state batteries are another potential solution to preventing thermal runaway as they have excellent thermal stability. In this study, an electrochemical model for the all-solid-state lithium-ion batteries has been developed. For the purpose of maintaining efficient control algorithm development, the model was simplified. A sensitivity analysis was conducted to observe the model accuracy in the simplified models. It was concluded from the simulation results that all the simplified models have sufficient accuracies in the voltage and capacity prediction; and it can serve as a useful tool for the state estimation.
Incorporating lithium-ion (Li-ion) batteries as an energy storage system in electric devices including electric vehicles brings about new challenges. In fact, the design of Li-ion batteries has to be optimized depending on each application specifications to improve the performance and safety of battery operation under each application and at the same time prevent the batteries from quick degradation. As a result, accurate models capable of predicting the behavior of Li-ion batteries under various operating conditions are necessary. Therefore, the main objective of this research is to develop a battery model that includes thermal heating and is suitable for large-sized prismatic cells used in electric vehicles. This works starts with developing a dual-extended Kalman filter based on an equivalent circuit model for the battery. The dual-extended Kalman filter simultaneously estimates the dynamic internal resistance and state of the charge of the battery. However, the estimated parameters are only the fitted values to the experimental data and may be non-physical. In addition, this filter is only valid for the operating conditions that it is validated against via experimental data. To overcome these issues, physics-based electrochemical models for Li-ion batteries are subsequently considered. One drawback of physics-based models is their high computational cost. In this work, two simplified one-dimensional physics-based models capable of predicting the output voltage of coin cells with less than 2.5% maximum error compared to the full-order model are developed. These models reduce the simulation computational time more than one order of magnitude. In addition to computational time, the accuracy of the physico-chemical model parameter estimates is a concern for physics-based models. Therefore, commercial LiFePO4 (LFP) and graphite electrodes are precisely modelled and characterized by fitting experimental data at different charge/discharge rates (C/5 to 5C). The temperature dependency of the kinetic and transport properties of LFP and graphite electrodes is also estimated by fitting experimental data at various temperatures (10 °C, 23 °C, 35 °C, and 45 °C). Since the spatial current and temperature variations in the large-sized prismatic cells are significant, one-dimensional models cannot be used for the modeling of these prismatic cells. In this work, a resistor network methodology is utilized to combine the one-dimensional models into a three-dimensional multi-layer model. The developed model is verified by comparing the simulated temperatures at the surface of the prismatic cell (consist of LFP as the positive and graphite as the negative electrode) to experimental data at different charge/discharge rates (1C, 2C, 3C, and 5C). Using the developed model the effect of tab size and location, and the current collector thickness, on the electrochemical characteristics of large-sized batteries is evaluated. It is shown that transferring tabs from the edges and the same side (common commercial design) to the center and opposite sides of the cell, and extending them as much as possible in width, lowers the non-uniformity variation in electrochemical current generation.
