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The behavior of a retired lithium-ion battery (LIB) from its first-life in an electric aircraft (EA) to its second-life in a solar photovoltaic (PV) system for a net-zero electricity residential home is studied. The first part of this study presents the design and sizing of a battery energy storage system (BESS), made from retired LIBs, to store a portion of the PV generation for a typical home in Ohio. The home is connected to the grid, but the net electricity usage from the grid in one year is zero. The purpose of the BESS is to peak shaving, power arbitrage, reduce the home dependency on the grid, and increase the economic benefits. The sizing is determined based on the hourly data of the PV system generation, ambient temperature, irradiation, and home demand electricity. In the second part of this study, the retired LIB degradation rate and its remaining useful life in the BESS are estimated using an adopted empirical LIB model. The model includes the capacity-fade for both first-life and second-life of the LIB under various duty cycles. It is shown that the retired LIB from its first-life is still suitable to be used in the PV grid-tied battery (PVGB) system for another 10 years. The results of this study can potentially reduce the LIB cost for electric vehicles (EVs) and EAs because the retired LIBs from these applications still have value to serve for other applications such as PVGB systems for residential homes.

A geothermal heat exchanger (GHE) uses geothermal energy for heating or cooling residential places during winter or summer. Two different designs of GHEs, the straight pipe and coiled pipe designs, are evaluated in this study, and the effect of nanofluids as the working fluid is investigated. For this purpose, a mathematical model is developed, validated, and used to predict the temperature gain, heat gain, exergy gain, and pressure loss of the working fluid for different concentrations of additive ceramic nanoparticles of aluminum oxide (Al2O3) and magnesium oxide (MgO) in the working fluid. It is shown that the coiled pipe design has a better performance compared to the straight pipe design for GHEs. It is also shown how the temperature, heat gain, and exergy gain change with increasing the additive nanoparticles into the base fluid, which is water, while the pressure loss does not change significantly. The temperature gain increases about 60% when the volume fraction of nanoparticles in the base fluid reaches 2%. This also helps to improve the natural circulation of working fluid and the GHE may not need a circulating pump to run at low flowrates. It is also shown that the additive MgO nanoparticles are more effective than Al2O3 nanoparticles to improve the GHE performance.

Flexible lithium-ion batteries (LIBs) have a strong oncoming consumer market demand for use in wearable electronic devices, flexible smart electronics, roll-up displays, electronic shelf labels, active radio-frequency identification tags, implantable medical devices, and so forth. This market demand necessitates research and development of new flexible LIBs to fulfill the electrical energy and power requirements of these next-generation devices. In this study, we investigate the performance of a new flexible LIB made from semi-solid electrodes. The semi-solid electrodes are made by adding a mixture of electrode active material and conductive material to the organic liquid electrode. This gives dense and viscous slurry so that all solid particles can move by acting pressure, shear, or bending forces to the battery. To study the performance of this battery we develop a 3D heterogeneous mathematical model that considers all necessary transport phenomena including the charge and mass transfer and electrochemical reactions at the continuum mechanics level on the reconstructed 3D structure of semi-solid electrodes. The finite element analysis (FEA) method was used to solve the governing equations using the comsol multiphysics software package. The model is validated using experimental data for the flexible LIB made in the lab. Based on the developed model, several studies are conducted to understand the effect of the battery discharge rate and the operating temperature on the battery capacity. These studies recommend an operational range for the temperature and discharge rate for this flexible LIB.

Flexible Li-ion batteries (LIBs) have a strong oncoming consumer market demand for use in wearable electronic devices, flexible smart electronics, roll-up displays, electronic shelf labels, active radio-frequency identification tags, and implantable medical devices. This market demand necessitates research and development of flexible LIBs in order to fulfill the power requirements of these next-generation devices. In this study, the performance of semi solid anode for flexible Lithiumion battery was investigated through a mathematical model in order to reduce the number of experiments and to achieve the desired energy capacity of the battery. This model is a multiphysics three-dimensional heterogeneous model where all necessary transport phenomena including the charge and mass transfer and electrochemical reactions are considered at continuum mechanics level. COMSOL Multiphysics software is used to solve governing equations numerically using a finite element method. This model is for a half-cell simulation, and by using experimental results obtained in the lab. The maximum specific discharge capacity of the simulation Graphite/Li half-cell and LCO/Li reached up to 248(mAh/g) and 128(mAh/g), respectively, compared to the values received in the experimental test of ∼240 (mAh/g) for Graphite/Li and 120 (mAh/g) for LCO/Li. Overall, the simulation results were in acceptable agreement with those of the experiment. Parametric study was also performed to study the effect of adjustable parameters on the performance of both half cells. The difference in the discharge capacity was observed showing higher values at higher cell temperature and lower c-rate.

The behavior of retired lithium-ion battery (LIB) from its first-life application such as electric vehicles and electric aircraft for its second-life in a solar photovoltaic (PV) grid-tied system for residential applications is studied through mathematical modeling. The rate of capacity-fade and the useful remaining life of the retired- or used-LIB particularly investigated in this paper. The first part of this paper presents the optimal size of a small-scale battery energy storage system (BESS) to store a part of the solar energy for postponing consumption in the near future for a typical home in Akron, Ohio. The LIBs in this study has lithium nickel manganese cobalt oxide (NMC) chemistry. The sizing is determined based on a set of PV panels, power rate of the BESS, and hourly data of temperatures, irradiation and home demand load. Using PVWatts® Calculator from National Renewable Energy Laboratory (NREL), the hourly PV performance data of the PV generation system is obtained. In this study, the home is connected to the grid, but the net energy usage from the grid in one year is zero. The duty-cycle of the PV generation is obtained in order to design a LIB energy storage system using calculations of the PV system hourly energy production. The difference between the residential home demand and PV generation is used to evaluate the excess energy that charges the battery and is sold to the electric grid. In the second part, the retired- or the used-battery degradation rate and its remaining useful second-life in the BESS are estimated using an empirical battery model. This model includes the capacity-fade of the LIB for both first- and second-life applications under different operating and environmental conditions. It is shown that a used-LIB from first-life applications is still suitable to be used for this system. The results show that the investigated used-LIB is capable of being in-service for another 10 years in the PV system for residential application. The results of this paper can potentially reduce the battery cost for electric vehicles and electric aircraft because the retired battery from these applications have still value to serve for another applications such as PV system for residential homes. Since this study is based on mathematical modeling, several assumptions have been made in the model. Although the results of mathematical modeling is very promising, these results should be proved experimentally. The experimental studies is out of the scope of this paper.

Among many types of all-solid-state lithium batteries (ASSLBs), the one based on argyrodite crystalline electrolyte is considered as one of the most promising batteries because of their safety and high energy density. Significant efforts have been devoted toward developing argyrodite-type ASSLBs, but the commercialization of these batteries still needs to resolve some scientific and technical problems. Two problems that need to be addressed are reducing the interfacial resistance between the electrolyte and electrode active materials and minimizing the reaction between the electrolyte and electrode active materials. One method to solve these two problems is to coat the electrode active material with a material which is compatible with argyrodite electrolyte. The aims of this paper are (1) to compare two methods of synthesizing and coating of cathode active material and (2) to evaluate the capacity and cycling performance of the coated active material. In this study the emphasis is on lithium niobate (LiNbO3) as the coating material and LiNi0.85Mn0.1Co0.05O2 (NMC) as the nickel-rich cathode active material.

A geothermal heat exchanger (GHE) uses the geothermal energy for heating or cooling of residential places during winter or summer. Two different designs of GHEs, the straight-pipe and coiled-pipe designs, are evaluated in this study, and the effect of nanofluid as the working fluid is investigated. For this purpose, a mathematical model is developed, validated, and used to predict the temperature gain, heat gain, exergy gain, and pressure loss of the working fluid for different concentration of additive ceramic nanoparticles (Al2O3 and MgO) into the working fluid. It is shown that the coiled-pipe design has better performance compared to the straight-pipe design for GHEs. It also shown that how the temperature, heat gain and exergy gain change with increasing the additive nanoparticles into the base-fluid (water), while the pressure loss does not change significantly. The temperature gain increases about 60% when the volume fraction of nanoparticles in the base-fluid reaches 2%. This also helps to improve the natural circulation of working fluid and the GHE may not need a circulating pump to run at low flow rates. It is also shown that the additive MgO nanoparticles is more effective than Al2O3 nanoparticles to improve the GHE performance.

Some lithium-ion batteries (LIBs) applications are mobile and stationary energy storage systems such as electric vehicles (full electric, hybrid and plug-in hybrid), different types of aircraft, and renewable energy technologies. LIBs can play a tremendous role in replacing the considerable dependence of nations on fossil fuels due to the high storage energy density of renewable energy alternatives. They also have a high cost associated with the material costs, as well as the other manufacturing costs. The environmental impact of manufacturing and disposing lithium-ion batteries has triggered actions to reduce the resulting impact by recycling batteries. Degradation of LIBs is always a concern for any application. To predict the life of cells correctly, it is more efficient to cover all mechanisms leading to capacity-fade or resistance growth. This study discusses the degradation rate of a LIB at two stages of life for both first- and second-uses. Empirical models can be used to measure capacity-fade, resulting from the battery degradation. The duty-cycle of the commercial LIB for a typical passenger aircraft, such as the Bombardier CRJ200, was obtained. For this purpose, the velocity and altitude of the aircraft were monitored during a typical flight, and the instantaneous mechanical power of the aircraft was obtained by modeling. Then, the duty-cycle of a LIB cell in the battery pack was yielded. The life prediction of the LIB in electrical energy storage for aircraft was studied. Although many studies have been done to evaluate performance and durability of LIB cells and packs for vehicle applications, there are very few studies of the application of LIBs in electric and hybrid aircraft. The degradation rate of the battery for a typical lightweight passenger aircraft with a flight range of less than 1000 km was then presented by using an empirical modeling method. The results showed that the A123 battery (20 Ah) degraded after 6 months at 45°C and 80% State of charge (SOC) and after 1.8 years at 45°C and 80% depth of discharge (DOD) by assuming that the battery should be retired when the rate of degradation reaches 15% of its nominal capacity. It was found that a retired first-use LIB cell is durable enough to be utilized in many second-use applications which can have lots of environmental benefits. Several items related to second use of LIBs will be discussed in this paper.

Steel pipeline in the oil and gas industry is subject to complex stress-strain due to soil movement along the pipes and internal pressure. The induced longitudinal strains due to soil movement along the pipe and the induced elasto-plastic local strain distribution are shown to impact the pipeline corrosion. In this work, we study the effect of defect geometry and density along the pipe on the local stress-strain distribution and subsequent local corrosion activity. Small strain von Mises yielding criteria is used and corrosion potential, anodic current density, and cathodic current density are characterized and used for this study by looking at the center to edge ratio.

Solid state electrolytes are promising materials for use in lithium-ion batteries for applications in electric vehicles and aircraft. One of the most promising solid electrolytes are the Argyrodite materials, Li6PS5X(X = Cl, Br, I). Among Argyrodites, Li6PS5Cl0.5Br0.5 crystalline material has high ionic conductivity, good processability and excellent electrochemical stability. It is reported in literature that the pelletization pressure and operating pressure and temperature significantly affect the ionic conductivity of argyrodite electrolytes and the cell performance. The focus of this paper is on Li6PS5Cl0.5Br0.5, a crystalline electrolyte material, and the goals are to systematically investigate effects of the pelletization pressure and operating pressure and temperature on the ionic conductivity of this material. The results of this study help to understand the range of pelletization, and operating pressures of all-solid-state lithium sulfur batteries made with Li6PS5Cl0.5Br0.5 crystalline electrolyte material.

In recent years, autonomous vehicles are at the forefront of the vehicle industry’s attention. Due to the fact that autonomous vehicles are driverless, the safety of these type of vehicles is more important to ensure the passengers safety. To improve the vehicle safety, intelligent tires can be used to provide tire and tire-pavement condition information to the autonomous vehicle control system. For this purpose, intelligent tires are equipped with different sensors such as temperature, pressure, wear and friction. These sensors need a sustainable and reliable power source so that the autonomous vehicle control system has access to the tire information at any conditions. Energy harvesters are proven to be applicable for tire waste strain energy harvesting to provide power for small on-board electronics. In this paper a strain-based energy harvester with the use of piezoelectric material is built and experimentally tested. A measurement system with wireless communication is also developed for online reading of the piezoelectric voltage and power. It is experimentally observed that the generated power by the piezoelectric energy harvester is enough to run the sensors tire. The effects of tire inflation pressure and normal load are also studied on the piezoelectric energy harvester (PEH) output voltage.

A numerical model is developed to predict the performance of a microchannel methanol steam reformer with different catalyst layer configurations to produce hydrogen-rich syngas for a high temperature polymer electrolyte membrane fuel cell (HT-PEMFC). A solution schema is developed to compare continuous catalyst layer configurations and various segmented catalyst layer configurations without any convergence issue in numerical analysis. In this work, heat is provided to the endothermic reforming-side via methanol combustion. The results show that higher heat transfer rates can be provided by applying segmented catalyst layer configurations thus, resulting in significant performance improvement of the microchannel methanol steam reformer. The results reveal that methanol conversion can be increased by ∼25% by using segmented catalyst layer configurations with less catalyst in the reforming and combustion sides. The results also indicate that even though there is no significant improvement in methanol conversion with increasing catalyst layer thickness, the greater catalyst layer thickness provides the advantage of reduced high temperature elevations across the reformer length. Overall, the segmented catalyst layer configurations can play an important role in designing a next generation of microchannel reformers for fuel cell power generation systems to maximize power, minimize reformer size, and decrease the required quantity of the catalyst.

The rapid spread of the SARS-CoV-2 virus that caused the COVID-19 disease, has highlighted our urgent need for sensitive, fast and accurate diagnostic technologies. In fact, one of the main challenges for flatting COVID-19 spread charts is the ability to accurately and rapidly identify asymptomatic cases that result in spreading the virus to close contacts. SARS-CoV-2 virus mutation is also relatively rapid, which makes the detection of COVID-19 diseases still crucial even after the vaccination. Conventional techniques, which are commercially available have focused on clinical manifestation, along with molecular and serological detection tools that can identify the SARS-CoV-2 virus however, owing to various disadvantages including low specificity and sensitivity, a quick, low cost and easy approach is needed for diagnosis of COVID-19. Scientists are now showing extensive interest in an effective portable and simple detection method to diagnose COVID-19. There are several novel methods and approaches that are considered viable advanced systems that can meet the demands. This study reviews the new approaches and sensing technologies that work on COVID-19 diagnosis for easy and successful detection of SARS-CoV-2 virus., Graphical abstract Image 1

Mathematical modeling of batteries has several advantages including (i) helping engineers to design the battery and the micro −/nanostructure of the battery electrodes to achieve the desired performance for a targeted applications, (ii) helping researchers to decrease the number of experiments, (iii) decreasing the time and cost of the battery development, and (iv) fundamental understanding the phenomena occurring in the battery. There are many types of batteries and nanobatteries as reported by different researchers. Although the development of a general mathematical model that can cover all types of batteries may not be practical, there are some physical and chemical phenomena that may be common in all batteries. In this chapter a physics-based, continuum-scale modeling of batteries, with focus on rechargeable lithium-ion batteries, is presented.

Large-sized lithium-ion battery (LIB) mathematical models are critical in design of cells, packs, and their associated thermal management systems. A high-fidelity fully coupled electrochemical-thermal model for a commercial 20 Ah LIB is developed to simulate the distribution of electrochemical and thermal variables three-dimensionally (3D) through 48 electrode layers in the pouch cell. As a new feature, the details of heat generation and voltage drop due to the tab, current collectors, and associated contact resistances are included in the developed model. A series of galvanostatic charge/discharge tests at operating rates ranging from 1C (20 A) to 5C (100 A) and at room temperature is conducted on the pouch cell and the output voltage and temperature distribution are recorded. The developed model voltage and temperature distribution predictions are successfully compared against the experimental data, demonstrating the accuracy of the model. As a key finding in this work, it is found that self-heating is the main contributor for electrochemical performance improvement in large-sized LIBs over small cells. This is due to the improved kinetic and transport properties of LIB electrodes at elevated temperatures. It is also demonstrated that the temperature variation between the surface and center layers of a pouch cell is not significant at a maximum difference of about 1.7 °C for charge/discharge rates up to 5C (100 A). As a result of this finding, it is suggested that a single temperature measurement close to the tabs at the battery surface would be sufficient for thermal management development and control purposes.

A steady state multiphysics model of a microchannel methanol reformer for hydrogen production was developed and validated to study the effects of catalyst layer structural parameters and heat supply strategies on the reformer performance. The hydrogen generated by the studied reformer was designated for use in high-temperature proton exchange membrane (HT-PEM) fuel cells. The dimensions of the reformer and inlet flow rate of methanol were selected to produce enough hydrogen to feed fuel cells in the 100 to 500 W range. The study considered a 2-dimensional domain for the thin coating of the reforming-catalyst to account for the internal diffusion limitations and the coating layer structural parameters. The multicomponent Maxwell–Stefan diffusion equation was implemented to account for diffusion fluxes inside the porous structure of the catalyst. The multiphysics model was validated using the reported experimental data by implementing four different reaction kinetics models of methanol steam reforming. The ...

Lithium-ion batteries (LIBs) dominate the industry of rechargeable batteries in recent years due to their advantages, including high energy and power density and relatively long lifespan. Despite these advantages, the disposal of spent LIBs into the ground is harmful to the environment, which needs to be addressed by recycling spent LIBs. The available recycling methods for spent LIBs such as pyrometallurgy and hydrometallurgy focus only on collecting valuable elements from the spent LIBs. The direct physical recycling method may be more economical than the other two methods if the mixed cathode and anode active materials are separated, directly regenerated, and then used to make new LIBs. The first obstacle in this method is the separation of different types of spent active materials that came in the form of micro-sized powder (filter cake). This study aims to separate the mixture of cathode and anode active materials by adopting Stokes' law. The focus is on the physical separation rather than the thermal or chemical separation methods to avoid damaging the morphology and composition of electrode active materials. The proposed mathematical model shows how fast and effectively different electrode materials can be separated by adjusting the heavy liquid density. For validation, several experiments are conducted to separate the cathode active materials (LiCoO2, LiFePO4, LiNi0.8Co0.15Al0.05O2, LiNi1/3Co1/3Mn1/3O2, and LiMn2O4) and the anode active material (Graphite) from each other. Overall, this study shows how rapidly and effectively (high purity) electrode active materials can be separated without damaging the morphology and the composition of electrode active materials.

The accuracy of state of health (SOH) estimation function in battery management systems is an essential factor for ensuring the safety and reliability of battery systems in electric aircraft. Most common SOH estimation approaches are model-based and work with constant model parameters. However, the model parameters vary by the change in operating temperature and state of charge (SOC). The variation of model parameters has adverse impact on the accuracy of battery state's estimation if they are not updated. In this paper, an accurate online parameter estimation method is proposed for lithium-ion batteries (LIBs) to increase the accuracy of the battery model. A more accurate model for the battery leads to a more accurate SOC and SOH estimation. An adaptive sliding observer is developed to estimate the SOC and capacity based on the proposed parameter estimator. An adaptive SOH estimation scheme is proposed to mitigate the temperature variation effect on the accuracy of the SOH estimation. The experimental results verify the effectiveness of the proposed parameter estimator along with the adaptive sliding observer on achieving accurate estimation of SOC and capacity. The proposed adaptive SOH shows good agreement with experiments by less than 1.3% estimation error at different operating temperature conditions.

Heat generation in lithium-ion batteries (LIBs), different in nominal battery capacity and electrode materials (battery chemistry), is studied at various charge and discharge rates through the multiphysics modeling and computer simulation. The model is validated using experimental results obtained in lab and the results reported by other researchers in literature. All sources of heat generation – including reversible heat generation and irreversible heat generation due to activation, concentration, and ohmic (electronic and ionic) polarizations – in LIBs with graphite/LiFePO4, graphite/LiMn2O4, and graphite/LiCoO2 electrode materials are quantified and the effects of the battery nominal capacity at various charge and discharge rates are studied. This study determines which sources of heat generation are significant and which sources of heat generation are negligible at different LIBs design and operating conditions. The contribution of LIB’s different components including cathode, anode, separator, and current collectors in heat generation in LIBs is also determined. The results of this study assists battery engineers and researchers to characterize the thermal behavior of LIBs and have a much more exact prediction over the battery heat generation, leading to designing effective thermal management systems and providing accurate battery management systems for different applications of LIBs as well as cell design optimization and operation.

In this study, synchrotron X-ray nano-computed tomography at Advanced Photon Source in Argonne National Laboratory has been employed to reconstruct real 3D active particle morphology of a LiMn 2 O 4 (LMO) electrode commonly used in lithium-ion batteries (LIBs). For the first time, carbon-doped binder domain (CBD) has been included in the electrode structure as a 108 nm thick uniform layer using image processing technique. With this unique model, stress generated inside four LMO particles with a uniform layer of CBD has been simulated, demonstrating its strong dependence on local morphology (surface concavity and convexity), and the mechanical properties of CBD such as Young’s modulus. Specifically, high levels of stress have been found in vicinity of particle’s center or near surface concave regions, however, much lower than the material failure limits even after discharging at the rate as high as 5C. On the other hand, the stress inside CBD has reached its mechanical limits when discharged at 5C, suggesting that it can potentially lead to failure by plastic deformation. The findings in this study highlight the importance of modeling LIB active particles with CBD and its appropriate compositional design and development to prevent the loss of electrical connectivity of the active particles from the percolated solid network and power losses due to CBD failure.

A new model that keeps all major advantages of the single-particle model of lithium-ion batteries (LIBs) and includes three-dimensional structure of the electrode was developed. Unlike the single spherical particle, this model considers a small volume element of an electrode, called the representative volume element (RVE), which represents the real electrode structure. The advantages of using RVE as the model geometry were demonstrated for a typical LIB electrode consisting of nano-particle LiFePO4 (LFP) active material. The three-dimensional morphology of the LFP electrode was reconstructed using a synchrotron X-ray nano-computed tomography at the Advanced Photon Source of the Argonne National. A 27 μm3 cube from reconstructed structure was chosen as the RVE for the simulation purposes. The model was employed to predict the voltage curve in a half-cell during galvanostatic operations and validated with experimental data. The simulation results showed that the distribution of lithium inside the electrode microstructure is very different from the results obtained based on the single-particle model. The range of lithium concentration is found to be much greater, successfully illustrating the effect of microstructure heterogeneity.

Lithium-ion batteries (LIBs) have driven the industry of rechargeable batteries in recent years due to their advantages such as high energy and power density and relatively long lifespan. Nevertheless, the dispose of spent LIBs has harmful impacts on the environment which needs to be addressed by recycling LIBs. However, none of the currently developed recycling processes is economical. The physical recycling process of LIBs may be economical if the cathode active materials can be separated, regenerated, and reused to make new LIBs. However, the first barrier for regeneration and reusing is the separation of different types of spent cathode active materials in the filter cake that are mixed with each other and come in the form of very fine powders with various sizes (< 30 μm) from the physical recycling process. The aim of this study is to separate the mixture of cathode active materials by adopting Stokes’ law. The focus will be only on mechanical separation with no thermal or chemical separation methods. For the validation, an experiment was designed and successfully performed where different types of spent cathode materials (e.g., LiCoO2, LiFePO4, and LiMn2O4) were separated from the spent anode materials (e.g., graphite) with high efficiency and reasonable time.

The quality of the collected data from a measurement system affects eventual decision making process. Therefore, the reliability of any measurement system is an important factor to be studied. Gauge repeatability and reproducibility (Gauge R&R) is the standard method to evaluate the measurement system and assess the adequacy of variation in the measurement data. Gauge R&R is a statistical tool which evaluates two main characteristics of the measurement system: repeatability and reproducibility. The Dynamic Mechanical Analysis (DMA) is a common measurement system for studying the dynamic mechanical properties of viscoelastic materials such as polymers. The newly developed High Frequency Dynamic Mechanical Analysis (HFDMA) is able to directly run the simple shear test at high frequencies without changing the specimen temperature. The complex shear modulus and damping factor of the viscoelastic materials are reported by the HFDMA system. In this study the uni-variable Gauge R&R study based on Analysis of Variance (ANOVA) is done on each measured characteristic of the HFDMA measurement system. The source of variations for each characteristic is distinguished. Then the multivariate Gauge R&R based on the Multivariate Analysis of Variance (MANOVA) is done and the percentage of multivariate Gauge R&R for the measurement with the multiple variables is reported. The results indicate that the HFDMA measurements are both repeatable and reproducible. Thus, the new HFDMA can be used as a measurement system to measure the mechanical properties of viscoelastic materials at high frequencies.

This paper presents the application of robotics for the disassembly of electric vehicle lithium-ion battery (LIB) packs for the purpose of recycling. Electric vehicle battery systems can be expensive and dangerous to disassemble, therefore making it cost inefficient to recycle them currently. Dangers associated with high voltage and thermal runaway make a robotic system suitable for this task, as the danger to technicians or workers is significantly reduced, and the cost to operate a robotic system would be potentially less expensive over the robots lifetime. The proposed method allows for the automated or semi-automated disassembly of electric vehicle LIB packs for the purpose of recycling. In order to understand the process, technicians were studied during the disassembly process, and the modes and operations were recorded. Various modes of interacting with the battery module were chosen and broken down into gripping and cutting operations. Operations involving cutting and gripping were chosen for experimentation, and custom end of arm tooling was designed for use in the disassembly process. Path planning was performed offline in both MATLAB/Simulink and ROBOGUIDE, and the simulation results were used to program the robot for experimental validation.

Drones or Unmanned Aerial Vehicles (UAV) are the aircraft controlled remotely by radio waves or autonomously and can fly without a pilot and passengers. Demands for drones with long flight times are increasing significantly in the personal and commercial applications. One of the main issues about drones is their power management. However, these devices are powered by a high energy density lithium battery, but a flight time range could be about 20–40 min. Increasing the battery energy storage capacity to achieve more flight time is not usually a good idea due to the additional weight in drones. In order to solve this issue, an Intelligent Battery Management System (IBMS) is proposed to predict the maximum available energy of the battery pack to make the best decision for finding the closest charging station depending on different weather conditions. In this study, lithium-ion battery with lithium titanite oxide (LTO) anode, as a fast charging and fast discharging battery, is used as the drone power supply. The proposed IBMS can not only increase the performance and life of the battery system but also it can estimate the battery cells state of charge (SOC) based on a system identification method. Results show that the proposed system has an accurate estimation of the maximum available energy, and therefore accurate flight time prediction to find the best recharging node for the drone.

In electric and hybrid-electric aircraft, the battery systems are usually composed of up to thousands of battery cells connected in series or parallel to provide the voltage and power/energy requirements. The inconsistent cells could affect the battery pack and its performance or even endanger electric and hybrid-electric aircraft security; thus, the early fault diagnosis of the battery system is essential. A well-designed battery management system along with a set of reliable voltage and current sensors is required to properly measure and control the cells operational variables in a large battery pack. In this study, based on the battery working mechanism, a new, fast, and robust fault diagnostic scheme is proposed for a lithium-ion battery (LIB) pack that can be employed for applications such as electric and hybrid-electric aircraft. In this method, some faults such as the overcharge, overdischarge occurring in LIB packs can be detected and isolated, based on some predefined factors gained from the battery models in healthy, overcharge, and overdischarge conditions. Finally, the effectiveness of the proposed fast fault diagnosis scheme is experimentally validated with LIBs under a typical flight cycle.