Improved thermal performance of a large laminated lithium-ion power battery by reciprocating air flow

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Thermal safety issues are increasingly critical for large-size laminated Lithium-Ion Batteries (LIBs). Despite a number of investigations conducted on the Battery Thermal Management System (BTMS) with reciprocating air-flow cooling, large laminated power LIBs are still not sufficiently investigated, particularly in the view of battery thermal characteristics. The present study investigates the thermal behaviors of an air-cooled NCM-type LIB (LiNi1−x−yCoxMnyO2 as cathode) from an experimental and systematic approach. The temperature distribution was acquired from different Depth of Discharge (DOD) by the infrared imaging (IR) technology. A reciprocating air-flow cooling method was proposed to restrict the temperature fluctuation and homogenize temperature distribution. Results showed that there was a remarkable temperature distribution phenomenon during the discharge process, the temperature distribution was affected by direction of air-flow. Forward air-flow (from current collector side to lower part of battery) was always recommended at the beginning of the discharge due to the thermal characteristics of the battery. After comprehensive consideration on battery temperature limit and cooling effect, the desired initial reversing timing was about 50% DOD at 3 C discharge rate. Different reversing strategies were investigated including isochronous cycles and aperiodic cycles. It was found that the temperature non-uniformity caused by heat accumulation and concentration was mitigated by reciprocating air-flow with optimized reversing strategy

Surface-to-Bulk Redox Coupling through Thermally Driven Li Redistribution in Li- and Mn-Rich Layered Cathode Materials.

Li- and Mn-rich (LMR) layered cathode materials have demonstrated impressive capacity and specific energy density thanks to their intertwined redox centers including transition metal cations and oxygen anions. Although tremendous efforts have been devoted to the investigation of the electrochemically driven redox evolution in LMR cathode at ambient temperature, their behavior under a mildly elevated temperature (up to ∼100 °C), with or without electrochemical driving force, remains largely unexplored. Here we show a systematic study of the thermally driven surface-to-bulk redox coupling effect in charged Li1.2Ni0.15Co0.1Mn0.55O2. We for the first time observed a charge transfer between the bulk oxygen anions and the surface transition metal cations under ∼100 °C, which is attributed to the thermally driven redistribution of Li ions. This finding highlights the nonequilibrium state and dynamic nature of the LMR material at deeply delithiated state upon a mild temperature perturbation

Vanadium redox flow batteries: Potentials and challenges of an emerging storage technology

open4noIn this paper an overview of Vanadium Redox Flow Battery technologies, architectures, applications and power electronic interfaces is given. These systems show promising features for energy storage in smart grid applications, where the intermittent power produced by renewable sources must meet strict load requests and economical opportunities. This paper reviews the vanadium-based technology for redox flow batteries and highlights its strengths and weaknesses, outlining the research lines that aim at taking it to full commercial success.openSpagnuolo, Giovanni, Guarnieri, Massimo; Mattavelli, Paolo; Petrone, Giovanni;Guarnieri, Massimo; Mattavelli, Paolo; Petrone, Giovanni; Spagnuolo, Giovann

Battery Insulation Performance Analysis in Electric Vehicles for the Improvement of Battery Lifetime

Battery is the main component both as an energy provider and as an interface for several systems in an electric vehicle. It has three important parameters: current, voltage and temperature that must be maintained as the battery can have a harmful reaction that can lead to overcurrent. The battery must also not overcharging or discharging for too long because it can cause a damage and affect its lifetime. Another error that can arise is sensor failure due to the interference or noise that can cause error in data reading. To prevent this problems, it needs a protection by means of isolation in operating the battery. In this research, planning in optimizing battery work was conducted by designing the process of detection and isolation of faults occurred in batteries, particularly lithium polymer battery to reach its more optimal and good performance. Battery modelling was needed as the parameter identification and Kalman Filter algorithm was applied to help to reduce the detection rate and fault isolation. The results of detection and isolation of overcurrent and sensor failure using Kalman Filter were found quite accurate. In overcurrent isolation, a discharge current of 6A was obtained from the maximum current limit of 10 A, and for sensor failure isolation, the Kalman Filter algorithm succeeded in improving the results of the previous reading

Redes de sensores de fibra ótica para monitorização in situ de baterias de ião de lítio

In this work, fiber optic sensor networks were developed to be integrated in commercially available lithium-ion batteries (cylindrical and prismatic) and pre-fabricated batteries in a laboratory environment (pouch cells), with the objective of monitoring in situ, operando and in real time, the internal and external variations of temperature and strain, under different environmental conditions and different charge and discharge rates. To this end, and in order to show the improved performance of fiber optic sensors in relation to the electronic ones, typically used in this type of application, their response time and resolution were compared. An improvement of 28% of the response time and a better resolution are attained with fiber optic sensors. Monitorization studies of the temperature and strain variations using fiber Bragg gratings (FBGs) in the cylindrical configuration have been made, as well as temperature and bi-directional strain variations in the prismatic configuration, under normal or abusive operating conditions, using the FBG method strain free. When the batteries were subjected to abusive operating conditions, it was evident that greater temperature and strain variations occur, being promoted by the rapid transport of lithium ions between the positive and negative electrodes. Due to the thermal expansion of the materials that compose the battery, its internal structure is an important parameter to consider and that can influence its behavior in terms of expansion and contraction. In order to monitor the thermal performance of lithium-ion prismatic batteries in different environmental conditions, studies were performed in which the battery operated at different discharge rates over different conditions of temperature and relative humidity, in order to simulate the performance of the battery in three distinct climates: cold, temperate, and dry. From these studies, the poor performance of this type of batteries in the cold climate, and consequent lower thermal performance was verified. A network of 37 FBG sensors has also been used to monitor the interfaces of a pack of 3 lithium polymer batteries connected in series. It was possible to perform a spatial and temporal thermal mapping under different discharge rates, and to identify areas that are more susceptible to the appearance of hot spots and that are capable of endanger its normal functioning. Hotter zones were detected near the current collectors, due to the higher density of lithium ions in this region. For the first time, the simultaneous discrimination of internal temperature and strain variations in lithium-ion batteries in the pouch cell configuration was carried out, through the incorporation of hybrid sensors, which combine the operational characteristics of the Fabry-Perot and FBG sensors. The evolution of the strain and temperature signals was followed by the proposed sensors and the largest strain variations were detected at the beginning of the discharge process, in the bottom position of the pouch cell. With the work developed in this Thesis, it is concluded that the integration of optical fiber sensors into lithium-ion batteries contributes to a better internal and external knowledge of the thermal performance and volume variations under different operating conditions. This might improve the safety conditions and optimize the design of the next generation of lithium-ion batteries.No presente trabalho, desenvolveram-se redes de sensores em fibra ótica para integrar em baterias comerciais de ião de lítio (cilíndricas e prismáticas) e em baterias pré-fabricadas em ambiente de laboratório (pouch cells), com o objetivo de monitorizar in situ, em funcionamento e em tempo real variações internas e externas de temperatura e deformação, sob diferentes condições ambientais e diferentes taxas de carga e descarga. Para tal, e de maneira a mostrar o melhor desempenho dos sensores de fibra ótica em relação aos eletrónicos tipicamente usados neste tipo de aplicação, os seus tempos de resposta e resolução foram comparados, obtendo-se uma melhoria de 28% do tempo de resposta e uma resolução superior com os sensores em fibra ótica. Foram feitos estudos da monitorização de variações de temperatura e deformação através de redes de Bragg em fibra (FBG) na configuração cilíndrica e variações de temperatura e deformação bidirecional na configuração prismática, aquando do seu funcionamento em condições normais e abusivas, através do método FBG strain-free. Quando as baterias foram submetidas a condições operacionais abusivas, ficou evidente que ocorrem maiores variações de temperatura e de deformação, sendo promovidas pelo rápido transporte dos iões de lítio entre os elétrodos positivo e negativo. Devido à expansão térmica dos materiais que compõem a bateria, a sua estrutura interna é um importante parâmetro a ter em consideração e que pode influenciar o seu comportamento em termos de expansão e contração. A fim de monitorizar o desempenho térmico de baterias prismáticas de ião de lítio em diferentes condições ambientais, realizaram-se estudos nos quais a bateria operou sob diferentes taxas de descarga em diferentes condições de temperatura e humidade relativa, por forma a simular o desempenho da bateria em três climas distintos: frio, temperado e seco. Destes estudos, constatou-se o fraco desempenho deste tipo de baterias no clima frio, e consequente inferior desempenho térmico. Uma rede de 37 sensores FBG foi ainda usada para monitorizar as interfaces de um pack de 3 baterias poliméricas de lítio, conectadas em série. Foi possível realizar um mapa térmico espacio-temporal para diferentes taxas de descarga, e identificar as zonas mais suscetíveis ao aparecimento de pontos quentes e capazes de colocar em risco o seu normal funcionamento. As zonas mais quentes foram detetadas próximas dos coletores de corrente, devido à superior densidade dos iões de lítio nesta região. Pela primeira vez, foi realizada a discriminação simultânea de variações internas de temperatura e deformação em baterias de ião lítio na configuração pouch cell, através da incorporação de sensores híbridos, que combinam as características operacionais dos sensores Fabry-Perot e FBG. A evolução da deformação e temperatura foi seguida pelos sensores propostos e as maiores variações de deformação foram detetadas no início do processo de descarga, na posição inferior da pouch cell. Com o trabalho desenvolvido nesta Tese, conclui-se que a integração de sensores em fibra ótica em baterias de ião de lítio contribui para um melhor conhecimento, interno e externo, do desempenho térmico e de variações de volume sob diferentes condições de funcionamento. Assim, poder-se-á melhorar as condições de segurança e otimizar o design da próxima geração de baterias de ião de lítio.Programa Doutoral em Engenharia Físic

ENERGY REDUCTION IN AUTOMOTIVE PAINT SHOPS A REVIEW OF HYBRID/ELECTRIC VEHICLE BATTERY MANUFACTURING

Automotive industry is facing fundamental challenges due to the rapid depletion of fossil fuels, energy saving and environmental concerns. The need of sustainable energy development has motivated the research of energy reduction and renewable energy sources. Efficient use of energy in vehicle manufacturing is demanded, as well as an alternative energy source to replace gasoline powered engines. In this thesis, we introduce a case study at an automotive paint shop, where the largest amount of energy consumption of an automotive assembly plant takes place. Additionally, we present a summary of recent advances in the area of hybrid and electrical vehicles battery manufacturing, review commonly used battery technologies, their manufacturing processes, and related recycling and environmental issues. Our study shows that energy consumption in paint shops can be reduced substantially by selecting the appropriate repair capacity, reducing the number of repainted jobs and consuming less material and energy. Also, it is seen that considerable effort needs to be devoted to the development of batteries for hybrid and electric vehicles in the near future, which will make this area challenging and research opportunities promising

Resilient and Real-time Control for the Optimum Management of Hybrid Energy Storage Systems with Distributed Dynamic Demands

A continuous increase in demands from the utility grid and traction applications have steered public attention toward the integration of energy storage (ES) and hybrid ES (HESS) solutions. Modern technologies are no longer limited to batteries, but can include supercapacitors (SC) and flywheel electromechanical ES well. However, insufficient control and algorithms to monitor these devices can result in a wide range of operational issues. A modern day control platform must have a deep understanding of the source. In this dissertation, specialized modular Energy Storage Management Controllers (ESMC) were developed to interface with a variety of ES devices. The EMSC provides the capability to individually monitor and control a wide range of different ES, enabling the extraction of an ES module within a series array to charge or conduct maintenance, while remaining storage can still function to serve a demand. Enhancements and testing of the ESMC are explored in not only interfacing of multiple ES and HESS, but also as a platform to improve management algorithms. There is an imperative need to provide a bridge between the depth of the electrochemical physics of the battery and the power engineering sector, a feat which was accomplished over the course of this work. First, the ESMC was tested on a lead acid battery array to verify its capabilities. Next, physics-based models of lead acid and lithium ion batteries lead to the improvement of both online battery management and established multiple metrics to assess their lifetime, or state of health. Three unique HESS were then tested and evaluated for different applications and purposes. First, a hybrid battery and SC HESS was designed and tested for shipboard power systems. Next, a lithium ion battery and SC HESS was utilized for an electric vehicle application, with the goal to reduce cycling on the battery. Finally, a lead acid battery and flywheel ES HESS was analyzed for how the inclusion of a battery can provide a dramatic improvement in the power quality versus flywheel ES alone

Model migration neural network for predicting battery aging trajectories

Accurate prediction of batteries’ future degradation is a key solution to relief users’ anxiety on battery lifespan and electric vehicle’s driving range. Technical challenges arise from the highly nonlinear dynamics of battery aging. In this paper, a feed-forward migration neural network is proposed to predict the batteries’ aging trajectories. Specifically, a base model that describes the capacity decay over time is first established from the existed battery aging dataset. This base model is then transformed by an input-output slope-and-bias-correction (SBC) method structure to capture the degradation of target cell. To enhance the model’s nonlinear transfer capability, the SBC-model is further integrated into a four-layer neural network, and easily trained via the gradient correlation algorithm. The proposed migration neural network is experimentally verified with four different commercial batteries. The predicted RMSEs are all lower than 2.5% when using only the first 30% of aging trajectories for neural network training. In addition, illustrative results demonstrate that a small size feed-forward neural network (down to 1-5-5-1) is sufficient for battery aging trajectory prediction

Structural Batteries for Aeronautic Applications—State of the Art, Research Gaps and Technology Development Needs

Radical innovations for all aircraft systems and subsystems are needed for realizing future carbon-neutral aircraft, with hybrid-electric aircraft due to be delivered after 2035, initially in the regional aircraft segment of the industry. Electrical energy storage is one key element here, demanding safe, energy-dense, lightweight technologies. Combining load-bearing with energy storage capabilities to create multifunctional structural batteries is a promising way to minimize the detrimental impact of battery weight on the aircraft. However, despite the various concepts developed in recent years, their viability has been demonstrated mostly at the material or coupon level, leaving many open questions concerning their applicability to structural elements of a relevant size for implementation into the airframe. This review aims at providing an overview of recent approaches for structural batteries, assessing their multifunctional performance, and identifying gaps in technology development toward their introduction for commercial aeronautic applications. The main areas where substantial progress needs to be achieved are materials, for better energy storage capabilities; structural integration and aircraft design, for optimizing the mechanical-electrical performance and lifetime; aeronautically compatible manufacturing techniques; and the testing and monitoring of multifunctional structures. Finally, structural batteries will introduce novel aspects to the certification framework

Optimizing Aqueous Processing of Nickel-Rich Cathode Material in Ultra-Thick Lithium-Ion Batteries

Lithium-ion batteries (LIBs) have been an instrumental technology since their commercialization in the 1990s. Although much progress has been made in terms of cost and efficiency of production, several challenges remain. Notably, as LIB technology continues to be applied to the transportation sector for electrified mobility in the form of electric vehicles, the question of production ethics and environmental sustainability becomes paramount. The aim of this dissertation is to address some of these concerns in the form of cathode processing techniques. This dissertation focuses on optimization of aqueous processing applied to cathode active materials. First, a study demonstrating the feasibility of aqueous processing for ultra-thick nickel-rich cathode active material via phosphoric acid addition shows both mechanical and electrochemical improvements in aqueous processed full cells. This study is then expanded upon by pursuing structured cathode designs for improved high-rate discharge capacity in ultra-thick cathodes. An improved cathode structure is identified and shown to not only be mechanically robust but also improve the utilization and energy density of the overall battery. Next, drying mechanics of aqueous cathodes are investigated in a comparative study focused on the first stage of slurry drying. A 10X increase in drying rate is identified and benefits are discussed. Finally, polymer electrolytes and the potential of aqueous processing applied to solid-state LIBs is explored and techniques for determining optimal compositions are identified