Modeling temperature distribution in cylindrical lithium ion batteries for use in electric vehicle cooling system design

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2008.Includes bibliographical references (leaf 31).Recent advancements in lithium ion battery technology have made BEV's a more feasible alternative. However, some safety concerns still exist. While the energy density of lithium ion batteries has all but made them the premier electric vehicle (EV) battery choice, their potential to overheat and explode is a limiting factor. Beyond certain temperature thresholds, lithium ion batteries will experience what is known as thermal runaway. During thermal runaway, the temperature of the battery increases uncontrollably and fires and explosions can occur. For this reason, adequate thermal management is a necessity in bringing lithium ion battery powered vehicles to market. The purpose of this work is to 1) develop mathematical models for temperature distribution and heat transfer in cylindrical lithium-ion cells and battery packs, 2) derive the target heat transfer coefficient for an EV cooling system 3) analyze the key design parameters of EV thermal management systems, and, ultimately, 4) determine the method of cooling necessary to prevent thermal runaway. The models are based on the fundamentals of heat transfer and are integrated into computer simulations for testing. Based on the models developed in this analysis, forced convection at the surface of the battery pack is not sufficient for preventing thermal runaway outside of minimum operational requirements (low ambient temperatures and discharge rates). For typical vehicle usage, a system in which the working fluid penetrates the pack is needed. There may be potential for a hybrid cooling system: one that relies on surface convection for less strenuous operation and strategically placed cooling channels for typical and extraneous operation.by Samuel Anthony Jasinski.S.B

Simultaneous Thermal and State-of-Charge Balancing of Batteries: A Review

The battery pack lifetime is severely affected by the State-of-Charge (SOC) and thermal imbalance among its cells, which is inevitable in large automotive batteries. In this review paper, the need of simultaneous thermal and SOC balancing is emphasized. Thermal and SOC balancing are two tightly coupled objectives. However, we argue here that it is possible to achieve these simultaneously by using a balancing device that enables the non-uniform use of cells, optimally using the brake regeneration phases and load variations in the drive cycle, and exploiting cell redundancy in the battery pack. The balancer must provide extra degree-of-freedom in control by distributing a large battery pack into smaller units to enable an independent cell/module-level control of a battery system

Safety of Lithium Nickel Cobalt Aluminum Oxide Battery Packs in Transit Bus Applications

The future of mass transportation is clearly moving toward the increased efficiency and greenhouse gas reduction of hybrid and electric vehicles. With the introduction of high-power/high-energy storage devices such as lithium ion battery systems serving as a key element in the system, valid safety and security concerns emerge. This is especially true when the attractive high-specific-energy and power-chemistry lithium nickel cobalt aluminum oxide (NCA) is used. This chemistry provides great performance but presents a safety and security risk when used in large quantities, such as for a large passenger bus. If triggered, the cell can completely fuel its own fire, and this triggering event occurs more easily than one may think. To assist engineers and technicians in this transfer from the use of primarily fossil fuels to battery energy storage on passenger buses, the Battery Application Technology Testing and Energy Research Laboratory (BATTERY) of the Thomas D. Larson Pennsylvania Transportation Institute (LTI) in the College of Engineering at The Pennsylvania State University partnered with advanced chemistry battery and material manufacturers to study the safety concerns of an NCA battery chemistry for use in transit buses. The research team ran various experiments on cells and modules, studying rarely considered thermal events or venting events. Special considerations were made to gather supporting information to help better understand what happens, and most importantly how to best mitigate these events and/or manage them when they occur on a passenger bus. The research team found that the greatest safety concern when using such a high-energy chemistry is ensuring passenger safety when a cell’s electrolyte boils and causes the ventilation of high-temperature toxic material. A cell-venting event can be triggered by a variety of scenarios with differing levels of likelihood. Also, though the duration of a venting event is relatively short, on the order of just a few seconds, the temperature of the venting material and cell is extremely high. During a venting event, the high-pressure, burning gases tend to burn holes in nearby packaging materials. Most interestingly, the team discovered that following a venting event the large-format cells tested immediately reached and remained at extremely high external skin temperatures for very long periods, on the order of hours. The majority of this report covers the testing designed to better understand how high-energy cells of this chemistry fail and what materials can be used to manage these failures in a way that increases passenger survivability

Improved Battery State Estimation Using Novel Sensing Techniques.

Lithium-ion batteries have been considered a great complement or substitute for gasoline engines due to their high energy and power density capabilities among other advantages. However, these types of energy storage devices are still yet not widespread, mainly because of their relatively high cost and safety issues, especially at elevated temperatures. This thesis extends existing methods of estimating critical battery states using model-based techniques augmented by real-time measurements from novel temperature and force sensors. Typically, temperature sensors are located near the edge of the battery, and away from the hottest core cell regions, which leads to slower response times and increased errors in the prediction of core temperatures. New sensor technology allows for flexible sensor placement at the cell surface between cells in a pack. This raises questions about the optimal locations of these sensors for best observability and temperature estimation. Using a validated model, which is developed and verified using experiments in laboratory fixtures that replicate vehicle pack conditions, it is shown that optimal sensor placement can lead to better and faster temperature estimation. Another equally important state is the state of health or the capacity fading of the cell. This thesis introduces a novel method of using force measurements for capacity fade estimation. Monitoring capacity is important for defining the range of electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs). Current capacity estimation techniques require a full discharge to monitor capacity. The proposed method can complement or replace current methods because it only requires a shallow discharge, which is especially useful in EVs and PHEVs. Using the accurate state estimation accomplished earlier, a method for downsizing a battery pack is shown to effectively reduce the number of cells in a pack without compromising safety. The influence on the battery performance (e.g. temperature, utilization, capacity fade, and cost) while downsizing and shifting the nominal operating SOC is demonstrated via simulations. The contributions in this thesis aim to make EVs, HEVs and PHEVs less costly while maintaining safety and reliability as more people are transitioning towards more environmentally friendly means of transportation.PhDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120815/1/nassimab_1.pd

Parametric Reduced-Order Models for the Structural Dynamics of Hybrid Electric Vehicle Batteries

A battery pack used in electrified vehicles consists of stacks of nominally identical cells mechanically coupled through foams and spacers. Because of these repeated substructures, the dynamic behavior of a pack is characterized by high modal density (HMD) regions with closely spaced natural frequencies. It is known that with frequencies of excitation in such a HMD region, small commonly occurring structural variations may lead to significant amplification of vibration responses in some cells compared to responses of the nominal design. Intense vibration responses may lead to high stresses and consequently lead to failure of the whole battery pack. Because cells are connected in series, the battery pack fails when one of the cells fails. Consequently, the maximum vibration response for cells is a key metric for the reliability of the battery pack. To characterize this dynamic behavior, it is necessary to conduct statistical analyses by calculating the vibration response amplitudes for a range of parameters quantifying these structural variations. Since it is time-consuming to conduct a single simulation with full-order finite element models with given structural variation levels, it is time prohibitive to conduct statistical analyses, which involve large numbers of simulations. Moreover, since different arrangements of different types of spacers affect the coupling of cells and are capable mitigating vibration responses of the battery pack, it is essential to search the optimal arrangement of spacers in designing process to improve the reliability of battery packs. Since the optimization of the arrangement of spacers involves considerable searching steps and the vibration response amplitudes are calculated at each step, the simulation time is desired to be reduced. This dissertation focuses on developing parametric reduced-order models (PROMs) to reduce the calculation time and enable statistical analyses and the optimization of the arrangement of spacers. The structural variations considered in this work are categorized into linear and nonlinear variations. Three linear structural variations are considered: prestress variation (PreV), cell-to-cell variation (C2CV), and spacer-to-spacer variation (S2SV). PreV comes from the preload applied on the battery pack. C2CV refers to each cell that has different structural characteristics compared to its nominal design. S2SV suggests different types of spacers. Two nonlinear structural variations are considered, which come from the nonlinear behavior in cells and foams. The modulus of the elasticity of cells and foams, which include porous material, increase nonlinearly due to the consumption of the porosity under deformation. PROMs are developed to capture all these linear and nonlinear structural variations simultaneously and to predict the vibration responses efficiently and accurately. The results predicted by PROMs are validated by comparison with the full-order model. The key contributions of this thesis are: (1) the development of novel PROMs for simultaneously capturing linear structural variations including PreV, C2CV, and S2SV, (2) the development of novel PROMs for capturing nonlinear behavior in cells and foams, and (3) the statistical analyses and optimization of the arrangement of spacers using PROMs. The statistical analyses show that the cell-to-cell variations can drastically amplify the vibration response of a cell. Also, the vibration response can be significantly mitigated with the optimized arrangement of spacers.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147723/1/jauching_1.pd

ANALYSIS AND OPTIMIZATION OF ELECTRICAL SYSTEMS IN A SOLAR CAR WITH APPLICATIONS TO GATO DEL SOL III-IV

Gato del Sol III, was powered by a solar array of 480 Silicon mono-crystalline photovoltaic cells. Maximum Power Point trackers efficiently made use of these cells and tracked the optimal load. The cells were mounted on a fiber glass and foam core composite shell. The shell rides on a lightweight aluminum space frame chassis, which is powered by a 95% efficient brushless DC motor. Gato del Sol IV was the University of Kentucky Solar Car Team’s (UKSCT) entry into the American Solar Car Challenge (ASC) 2010 event. The car makes use of 310 high density lithium-polymer batteries to account for a 5 kWh pack, enough to travel over 75 miles at 40 mph without power generated by the array. An in-house battery protection system and charge balancing system ensure safe and efficient use of the batteries. Various electrical sub-systems on the car communicate among each other via Controller Area Network (CAN). This real time data is then transmitted to an external computer via RF communication for data collection