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State Estimation and Thermal Fault Detection for Lithium-Ion Battery Packs: A Deep Neural Network ApproachNaguib, Mina Gamal January 2023 (has links)
Recently, lithium-ion batteries (LIBs) have achieved wide acceptance for various energy storage applications, such as electric vehicles (EVs) and smart grids. As a vital component in EVs, the performance of lithium-ion batteries in the last few decades has made significant progress. The development of a robust battery management system (BMS) has become a necessity to ensure the reliability and safety of battery packs. In addition, state of charge (SOC) estimation and thermal models with high-fidelity are essential to ensure efficient BMS performance.
The SOC of a LIB is an essential factor that should be reported to the vehicle’s electronic control unit and the driver. Inaccurate reported SOC impacts the reliability and safety of the lithium-ion battery packs (LIBP) and the vehicle. Different algorithms are used to estimate the SOC of a LIBP, including measurement-based, adaptive filters and observers, and data-driven; however, there is a gap in feasibility studies of running these algorithms for multi-cell LIBP on BMS microprocessors. On the other hand, temperature sensors are utilized to monitor the temperature of the cells in LIBPs. Using a temperature sensor for every cell is often impractical due to cost and wiring complexity. Robust temperature estimation models can replace physical sensors and help the fault detection algorithms by providing a redundant monitoring system.
In this thesis, an accurate SOC estimation and thermal modeling for lithium-ion batteries (LIBs) are presented using deep neural networks (DNNs). Firstly, two DNN-based SOC estimation algorithms, including a feedforward neural network (FNN) enhanced with external filters and a recurrent neural network with a long short-term memory layer (LSTM), are developed and benchmarked versus an extended Kalman filter (EKF) and EKF with recursive least squares filter (EKF-RLS) SOC estimation algorithms. The execution time of EKF, EKF-RLS, FNN, and LSTM SOC estimation algorithms with similar accuracy was found to be 0.24 ms, 0.25 ms, 0.14 ms, and 0.71 ms, respectively. The DNN SOC estimation algorithms were also demonstrated to have lower RAM use than the EKFs, with less than 1 kB RAM required to run one estimator.
The proposed FNN and LSTM models are also used to predict the surface temperature of different lithium-ion cells. These DNN models are shown to be capable of estimating temperature with less than 2 ⁰C root mean square error for challenging low ambient temperature drive cycles and just 0.3 ⁰C for 4C rate fast charging conditions. In addition, a DNN model which is trained to estimate the temperature of a new battery cell, is found to still have a very low error of just 0.8 ⁰C when tested on an aged cell.
Finally, an integrated physics, and neural network-based battery pack thermal model (LP+FNN) is developed and used to detect and identify different thermal faults of a LIBP. The proposed fault detection and identification method is validated using various thermal faults, including fan system failure, airflow lower and higher than setpoint, airflow blockage of submodule and temperature sensor reading faults. The proposed method is able to detect different cooling system faults within 10 to 35 minutes after fault occurrence. In addition, the proposed method demonstrated being capable of detecting temperature sensor reading offset and scale faults of ±3 ⁰C and ±0.15% or more, respectively with 100% accuracy. / Thesis / Doctor of Philosophy (PhD)
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Tailored Quasi-Solid-State Lithium-Ion Electrolytes for Low Temperature OperationsNestor R Levin (17584008) 10 December 2023 (has links)
<p dir="ltr">The thesis goal was to design a quasi-solid-state battery electrolyte, which was optimized to function at ambient as well as low temperatures. In the first project, an array of quasi-solid-state electrolytes were developed and compared. A series of electrochemical, spectroscopic, and thermal experiments in addition to imaging techniques determined a top performer as well as elucidated possible mechanistic explanations. This systematic study attempted to validate literature conclusions about the failure mechanisms governing batteries (solid-state batteries) at ultralow temperatures, while also offering hypothesis driven additional insight. The optimized electrolyte, which will be deemed as CSPE@2MMeTHF, performed well for several key reasons, traced to the co-solvent used (Me-THF), the salt concentration, and its formation of a stable and suitable cathode-electrolyte interphase. It was able to perform well at 25 °C, and down to -25 °C. The second part of the work, focused on further optimizing the electrolyte by removing a ‘polymer wetting/soaking’ step, removing a ceramic component, and pairing it with a recently discovered anodic electrode material. Given that narrowing the research gap for low temperatures requires both electrolyte and electrode design, it was important to consider this aspect of the problem as well. The cathodic electrode used for the first project, traditionally performs poorly at low temperatures, allowing for a suitable experimental control for the electrolyte. However, the new anodic electrode had two ways of storing lithium ions, as opposed to just one in the former, making it an attractive option for the stated goal of a low-temperature solid-state battery. This second project is akin to a ‘proof-of-concept’ work and there is much more room for further study, especially in preparing a full cell with the aforementioned electrodes cathode (LFP) and anode (NbWO) with the second SPE@51DMMeT electrolyte. In summary, this thesis shows method design to prepare solid-state electrolytes with portion of liquid, two successfully developed electrolyte systems for low temperatures, and a rigorous discussion of factors that affect electrochemical performance. Demonstrated research activities are of great value to defense as the current lithium-ion batteries does not perform well at subzero temperatures.</p>
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Om packmaterial för transport av litiumjonbatterier : Brandegenskaper och arbetsmiljö / On packing material for transport of lithium-ion batteries : Fire properties and working environmentHansson, Petter, Ohlsson, Sanna January 2022 (has links)
As the climate issue has affected most vehicle manufacturers, the number of electric cars in the world has increased in recent years. Scania's goal is that by 2030, 50 % of all their trucks sold in Europe will be powered by electricity. There are currently legal requirements for how transportation of batteries by road is allowed, depending on if the batteries are damaged, defective or prototype batteries. Scania currently has a method to transport these batteries. The working method consists of a safety box that is filled with the packing material Pyrobubbles in which the batteries are placed. However, Scania wants a better understanding of the function of Pyrobubbles, the safety box and its advantages and disadvantages, as well as whether there are better solutions. The work therefore intends to sort out these issues. In addition to reviewing the thermal properties of the materials, the work has been carried out from a SHE perspective on Scania’s request. This means that safety, health and the environment are taken into account. A literature study was conducted to investigate which alternative packaging materials were available as option to Pyrobubbles, as well as other manufacturers that are available for the safety box. Seven different packaging materials have been examined in the report, these are; absol, sorbix, vermiculite, sand, Pyrobubbles, glass- and stone wool. Two experimental studies were performed to investigate the properties of packing materials. All materials were tested in the cone calorimeter as three different experimental setups; dry, damp and inside a rust protection bag. Two full-scale experiments were also carried out where Pyrobubbles and rockwool were tested as packing material. In addition, a bow tie was created regarding the handling of packing material and an investigation of the ergonomics was conducted. The rust protection bag that is currently used at Scania to facilitate the packaging of Pyrobubbles contributes to unwanted heat release. The lowest heat release and best insulation capacity were measured for the sand. However, the sand is unmanageable to work with as it has a high density and contains carcinogenic particles. Rockwool is considered a good alternative to Pyrobubbles, which partly facilitates the work situation for employees and is also more accessible than Pyrobubbles. In order for rockwool to be accepted as a packing material, a certification of packing material and safety box must be done together, which applies to all new solutions. Keywords: Pyrobubbles, Lithium-ion battery, battery safety, ADR-S
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MECHANISTIC ROLE OF THERMAL EFFECTS ON LITHIUM PLATINGConner Fear (13171236) 28 July 2022 (has links)
<p> In the pursuit to enable the rapid charging of lithium-ion batteries, lithium plating at the anode poses one of the most significant challenges. Additionally, the heat generation that accompanies high rate battery operation in conjunction with non-uniform cooling and localized heating at tabs is known to result in thermal inhomogeneity. Such thermal anomalies in the absence of proper thermal management can instigate accelerated degradation in the cell. This work seeks to elucidate the link between thermal gradients and lithium plating in lithium-ion batteries using a combined experimental and simulation-based approach. First, we experimentally characterize the lithium plating phenomenon on graphite anodes under a wide variety of charging rates and temperatures to gain mechanistic insights into the processes at play. An in operando detection method for the onset of dendritic lithium plating is developed. Lithium plating regimes are identified as either nucleate or dendritic, which exhibit vast differences in reversibility. An operando method to quantify lithium stripping based on the rest phase voltage plateau is presented. Next, a model is employed to provide fundamental insights to the thermo-electrochemical interactions during charging in scenarios involving an externally imposed in-plane and inter-electrode thermal gradient. The relative importance of in-plane vs. inter-electrode thermal gradients to charging performance and cell degradation is necessary to inform future cell design and cooling systems for large-format cells, which are crucial for meeting the energy requirements of applications like electric vehicles. While in-plane thermal gradients strongly influence active material utilization, the lithium plating severity was found to be very similar to an isothermal case at the same mean temperature. By contrast, inter-electrode thermal gradients cause a shifting on the solid phase potential at each electrode during charging, related to the increase or decrease in overpotential due to local temperature variation. An experiment is then performed on a commercial multi-layer pouch cell, in which it was found that applied thermal gradients provide a slight reduction in lithium plating severity and degradation rate when compared to an isothermal cell at the same mean temperature. The presence of a thermal gradient causes heterogeneous lithium plating deposition within the cell, with colder regions experiencing higher quantities of plating and larger thermal gradients leading to more severe heterogeneity. </p>
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PHYSICS BASED DEGRADATION ANALYTICS IN ENERGY STORAGEVenkatesh Kabra (10531817) 04 December 2023 (has links)
<p dir="ltr">Li-ion batteries are ubiquitous in today’s world with portable electronics, EVs making inroads into daily lives, and electric aircraft at the cusp of becoming reality. These and many more applications revolutionize the world with improvements in batteries at scales from materials, manufacturing, electrode architectures, cell design, and protocols. The various challenges associated with the current generation of batteries include the fast-charging capabilities, economic return of the longevity of the battery, and thermal safety characteristics. The aging and degradation of LIBs appears to be a key pain point particularly when exposed to harsh operating temperature and fast charging conditions. LIBs undergo aging due to numerous chemical and physical degradation processes throughout their lifetime owing to their operation. These challenges are exacerbated by the presence of stringent operating conditions including extreme fast charging, and sub-zero temperature resulting in severe degradation and short cycle life. The LIBs also face challenges in their thermal stability characteristics, failing catastrophically when exposed to high temperature or mechanical abuse conditions. The onset and intensity of these thermal runaway behaviors are further modified when batteries undergo varied aging leading to increased heat and gas generation potentially causing fire or explosions. Overall, a comprehensive characterization to delineate the interconnected role and implications of operating extremes and electrode design on electrochemical performance, cell aging, and thermal runaway behavior is critical for better batteries. </p><p dir="ltr">To this end, the role of electrode microstructure in mitigating lithium plating behavior under various operating conditions, including extreme fast charging has been examined. Further, these multi-length scale characteristics of the electrode microstructure are explored via data-driven approaches to study the complex interaction of transport and kinetic limitations on the microstructure designs. A third study is undertaken for in-operando characterization of the LIB degradation, probing the multi-length scale degradation using pulse voltammetry. Here an accurate degradation descriptors dataset is identified and accurately parametrized, throughout its cycling lifespan. These aging behaviors are translated to physio-chemical degradation mechanisms via a reduced-order coupled electrochemical-thermal-aging interactions model. Lastly, the implication of aging behavior on thermal-safety interactions is delineated. Overall the dissertation is focused on developing a fundamental understanding of the LIB performance, degradation, and safety interactions.</p>
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Towards Development of Porous Polymeric Materials for Oil Absorption and Energy Storage DevicesZhan, Chi 05 June 2018 (has links)
No description available.
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Implementation of Machine Learning and Internal Temperature Sensors in Nail Penetration Testing of Lithium-ion BatteriesCasey M Jones (9607445) 13 June 2023 (has links)
<p>This work focuses on the collection and analysis of Lithium-ion battery operational and temperature data during nail penetration testing through two different experimental approaches. Raman spectroscopy, machine learning, and internal temperature sensors are used to collect and analyze data to further investigate the effects on cell operation during and after nail penetrations, and the feasibility of using this data to predict future performance.</p>
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<p>The first section of this work analyzes the effects on continued operation of a small Lithium-ion prismatic cell after nail penetration. Raman spectroscopy is used to examine the effects on the anode and cathode materials of cells that are cycled for different amounts of time after a nail puncture. Incremental capacity analysis is then used to corroborate the findings from the Raman analysis. The study finds that the operational capacity and lifetime of cells is greatly reduced due to the accelerated degradation caused by loss of material, uneven current distribution, and exposure to atmosphere. This leads into the study of using the magnitude and corresponding voltage of incremental capacity peaks after nail puncture to forecast the operation of damaged cells. A Gaussian process regression is used to predict discharge capacity of different cells that experience the same type of nail puncture. The results from this study show that the method is capable of making accurate predictions of cell discharge capacity even with the higher rate of variance in operation after nail puncture, showing the method of prediction has the potential to be implemented in devices such as battery management systems.</p>
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<p>The second section of this work proposes a method of inserting temperature sensors into commercially-available cylindrical cells to directly obtain internal temperature readings. Characterization tests are used to determine the effect on the operability of the modified cells after the sensors are inserted, and lifetime cycle testing is implemented to determine the long-term effects on cell performance. The results show the sensor insertion causes a small reduction in operational performance, and lifetime cycle testing shows the cells can operate near their optimal output for approximately 100-150 cycles. Modified cells are then used to monitor internal temperatures during nail penetration tests and how the amount of aging affects the temperature response. The results show that more aging in a cell causes higher temperatures during nail puncture, as well as a larger difference between internal and external temperatures, due mostly to the larger contribution of Joule heating caused by increased internal resistance.</p>
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Lithium Ion Battery Failure Detection Using Temperature Difference Between Internal Point and SurfaceWang, Renxiang 12 1900 (has links)
Indiana University-Purdue University Indianapolis (IUPUI) / Lithium-ion batteries are widely used for portable electronics due to high energy density, mature processing technology and reduced cost. However, their applications are somewhat limited by safety concerns. The lithium-ion battery users will take risks in burn or explosion which results from some internal components failure. So, a practical method is required urgently to find out the failures in early time. In this thesis, a new method based on temperature difference between internal point and surface (TDIS) of the battery is developed to detect the thermal failure especially the thermal runaway in early time. A lumped simple thermal model of a lithium-ion battery is developed based on TDIS. Heat transfer coefficients and heat capacity are determined from simultaneous measurements of the surface temperature and the internal temperature in cyclic constant current charging/discharging test. A look-up table of heating power in lithium ion battery is developed based on the lumped model and cyclic charging/discharging experimental results in normal operating condition. A failure detector is also built based on TDIS and reference heating power curve from the look-up table to detect aberrant heating power and bad parameters in transfer function of the lumped model. The TDIS method and TDIS detector is validated to be effective in thermal runaway detection in a thermal runway experiment. In the validation of thermal runway test, the system can find the abnormal heat generation before thermal runaway happens by detecting both abnormal heating power generation and parameter change in transfer function of thermal model of lithium ion batteries. The result of validation is compatible with the expectation of detector design. A simple and applicable detector is developed for lithium ion battery catastrophic failure detection.
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