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An electric pump-fed cycle can enable the electrical control of pump revolutions and rapidly vary the propellant flow rate. This paper proposes the pump control method as a flow control system of an electric pump-fed cycle. In order to evaluate the applicability of the designed flow control system, the test equipment that simulates an electric pump-fed cycle was constructed, including the Li-ion battery power system and communication instruments. The designed PID controller demonstrated rapid flow stabilization and robustness compared to the system without a controller. Meanwhile, under the initial pressurized condition in the run tank that simulated an engine start-up sequence, the controller response delay occurred was more than 500 ms. In addition, the dynamic loads, such as the water hammer effects and overshoot, were identified. The start-up sequence of an EP cycle was adjusted to alleviate those issues. Consequently, the supply stabilizing time and overshoot were adjusted to 400 ms and 1.7 %, respectively. This study can be the first step in utilizing an electric pump-fed cycle for the thrust control technology in the upper stage of a mission. • An electric pump-fed cycle has a simple system with an electric motor and battery system replacing a gas generator and turbine of a gas-generator cycle. • An electric pump-fed cycle can be used as a throttleable and restartable rocket engine technology, providing a rapid response enabled by the quick propellant feeding through an electrical signal control. • The pump control system with PID controller shortened the flow stabilizing in the experiments compared to the flow control system without the PID controller. • By adjusting the electric pump-fed cycle start-up sequence, it can effectively mitigate the water hammer and shorten the stabilizing time. [ABSTRACT FROM AUTHOR]

Electric cars are becoming increasingly popular, with the European Union and the United States administrations committed to making their share overwhelming by the end of this decade. In analogy, electric powerboats and aircraft are also being proposed. Here we show as hybrid electric vehicles (HEVs) have advantages vs. battery-only electric vehicles (BEVs) for all these applications. Adopting a hybrid propulsion system based on storing most of the energy in hydrogen, and producing electricity on board through a fuel cell (FC) stack, or an internal combustion engine (ICE) plus a generator, gives a much better techno-economic perspective, and reduced life cycle analysis CO 2 emissions, than the use of huge lithium-ion batteries. An HEV having plug-in capability and a relatively small battery permits pure electric operation on short travel, without the burden of huge batteries to deliver range. The battery of the HEV buffers the upstream hybrid generation system, which may recharge the battery and/or power directly the electric motor, and store the braking energy in ground vehicles. HEVs fuel energy storage and onboard electricity generation on demand permit reduced total mass of the propulsion system for the same design range as huge batteries. HEVs with ICE working on hydrogen offers the minimum total mass of the propulsion system, then HEVs with FC. This assessment is correct for the current liquid electrolyte batteries and the near-future solid-state electrolyte batteries, based on their energy density per unit mass, and the indirect emissions of batteries. • Hybrid electric propulsion systems are superior to battery electric. • Energy density of storage in hydrogen fuel is better than in a battery. • On-board energy storage improved with a fuel cell or combustion engine/generator systems. • Advantages are larger for aviation, smaller for road vehicles. [ABSTRACT FROM AUTHOR]

• A CFD fluid-solid coupling simulation model to study the temperature distribution of stator coils and inverter of an electric scroll compressor was developed and validated. • The temperature distribution of stator coils and inverter under different refrigerant conditions was simulated and analyzed. • The working reliability of stator coils and IGBT modules under the studied refrigeration conditions was checked. • The heat dissipation of IGBT modules and the proportion of heat exchange amount between different parts of compressor housing and suction gas were analyzed. In the electric scroll compressor for vehicle air conditioning, the heat generated by motor and inverter is mainly taken away by suction gas. It is necessary to maintain the working temperature of motor and inverter within a safe range to void overheat or burnout. The temperature distribution of motor and inverter under refrigeration conditions are studied using computational fluid dynamics (CFD) simulation in this paper. At first, a CFD fluid-solid coupling simulation model is developed and verified by temperature measurement experiment. The maximum deviation between the simulated temperature at three points on the compressor housing and the measured results does not exceed ±3°C. Then the velocity and pressure distribution of fluid domain, and the temperature distribution of solid domains including the compressor housing, the stator coils and insulated gate bipolar transistor (IGBT) modules are analyzed. Next, the effects of operation conditions on the maximum working temperature and temperature distribution unevenness of stator coils and IGBT modules are discussed in detail. In addition, the working reliability of IGBT modules under refrigeration conditions is checked and the heat dissipation of IGBT modules is analyzed. [ABSTRACT FROM AUTHOR]

The focus of this paper is to investigate the practicality of incorporating immersion cooling methods to mitigate the temperature elevation of motors utilized in hybrid aircraft. Air cooling, oil jacket cooling, slot-channel oil cooling and immersion cooling techniques are each applied to a permanent magnet synchronous motor. When a hybrid aircraft is operating, the amount of fuel it carries is limited and decreases over time. In this case, the normal operating time of the motor is investigated in this paper. The study shows that for the motors in this paper, immersion cooling is the most effective with a limited amount of coolant and takes the longest time to reach the upper temperature limit, which can be improved by 5.6 times compared to slot-channel cooling. This paper serves as a reference for the design of motors for hybrid aircraft utilizing immersion cooling technology. [ABSTRACT FROM AUTHOR]

Autonomous vehicles (AV) are expected to improve road safety and reduce traffic congestion by optimizing routes and reducing human errors. AVs have the potential to increase accessibility for people with disabilities and reduce the environmental impact of transportation. AVs require radio transmitters to communicate with other vehicles and infrastructure, external charging to power their electric motors, and communication equipment to receive real-time data about traffic and road conditions. Additionally, these requirements must be met for AVs to operate efficiently and conserve energy. Therefore, this work introduces a novel technique called energy-conservation guided route adaptation (EC-GRA) that aims to enhance the energy efficiency of connected vehicles. With the balance in energy adaptation for distinct purposes, the utilization rate is adjusted for communication and navigation. The complex decisions are confined to the energy availability and conservation factors required in an adaptive driving condition. This technique employs transfer learning to update the available and adaptable energy ratios under displacement-based route adaptations. In the learning process, the transfer and update states for displacement-aware decisions under varying scenarios are modeled. This study validates the state transitions involved in recommending energy utilization during both autonomous and guided driving scenarios. The results show that the proposed methodology exhibits superior performance compared to the currently available techniques. The EC-GRA under consideration has demonstrated an average energy conservation ratio of 45.58. The decision rate for this method is 0.63/navigation, while its energy utilization is 126.37 Joules. The number of failures observed in the proposed EC-GRA is 6/navigation, which represents an improvement over the existing approach. [ABSTRACT FROM AUTHOR]

In the last 20 years, the transportation sector has enabled the technology to evolve in its direction with both environmental and energy efficiency in the use of electric and fuel cell vehicles. The two important components of these vehicles are the batteries and electric motors. The batteries are produced within a certain life cycle, and unfortunately it is not possible to use them without conversion/recycling. In this study, the crucial importance of battery recycling/reusing is underliying and last researches will be given about battery recycling, above next ten years. Recommendations and future forseen advices will be presented about the current state of battery recycling technology, how recycling systems exist in different batteries, and the future of battery recycling standart. As a result, battery recycling and reusing for fuel cell and electric vehicles is considered to be an important keypoint in terms of both envirenmontial, economical and technologial menner for the transportation sector in the next decades. • Battery recycling, which will play a key role in the next decade for vehicles, is figured out. • Safety on recycling techniques were expressed crucially. • Fuel Cell Electric Vehicles batteries and platinum minerals importance is discussed. • Newer and future aspects on battery recycling/reusing of EVs and FCEVs were added. [ABSTRACT FROM AUTHOR]

In this work, various electrochemical cells were developed from carbons recovered from mechanical seal carbons, electric motor brush carbons (MBC) and AA battery carbons (BC). After the different types of carbons were conditioned, three electrooxidation devices were assembled, where the carbons were used as anode, and the cathode was stainless steel 304 SS. In each of the devices, three different separations between the anode and the cathode were considered: 1/8”, 3/16” and 1/4”. The electrical characterization of each of the cells was carried out using a sodium bisulfite solution (NaHSO3 ), with and without system agitation. The results indicated that agitation was not a factor that significantly affected the voltage conduction. The voltametric behavior revealed that the highest current density was presented by the MBC (39.2 mA/cm² ) for a separation of 1/8”, followed by the BC (17.45 mA/cm² ) for the same separation. To select the best arrangement, the premature wear of the anode was also considered. In this instance the BC did not present carbon detachment, so it was selected to carry out the degradation of 17-α-ethinyl estradiol. The degradation efficiency was 74% in 2 h. The identification of by-products by gas chromatography coupled to mass spectrometry revealed the majority presence of carboxylic acids. [ABSTRACT FROM AUTHOR]

Machining-based deformation processing is used to produce metal foil and flat wire (strip) with suitable properties and quality for electrical power and renewable energy applications. In contrast to conventional multistage rolling, the strip is produced in a single-step and with much less process energy. Examples are presented from metal systems of varied workability, and strip product scale in terms of size and production rate. By utilizing the large-strain deformation intrinsic to cutting, bulk strip with ultrafine-grained microstructure, and crystallographic shear-texture favourable for formability, are achieved. Implications for production of commercial strip for electric motor applications and battery electrodes are discussed. [ABSTRACT FROM AUTHOR]

X-type samarium-cadmium co-substituted hexaferrite with compositions Ba 2-x Sm x Co 2 Cd y Fe 28-y O 46 (0.00 ≤ x ≤ 0.08, and 0 ≤ y ≤ 0.4) were prepared at 1340 °C using a simple heat treatment technique. All heated samples were characterized using FTIR, XRD, SEM, VSM, Mӧssbauer, and low-frequency dielectric measurements. XRD analysis of prepared samples shows the formation of X as a major phase along with hematite. The M S value varied from 67.01 Am2/kg to 50.43 Am2/kg; whereas the H c value changed from 2.95 kA/m to 6.17 kA/m, A high value of M S (67.01 Am2/kg) is observed in the pure sample, and a very low value of H c (2.95 kA/m) is observed for x = 0.06, y = 0.3 compositions, but Mr/Ms < 0.5 confirm the multi-domain nature of prepared hexaferrites. Hysteresis loops of all samples are narrow, and confirmed that formed samples belong to magnetically soft. Mössbauer spectra of the three samples (S1, S3, and S5) show the existence of doublets. Significantly low values of coercivity, retentivity, and loss tangent in Sm–Cd substituted samples signified those prepared materials can be used to design electromagnets, transformer cores, electric motors, and maybe a potential candidate for lossless low-frequency applications. [ABSTRACT FROM AUTHOR]

• A methodology for fan efficiency deployment was proposed. • The axial flow maldistribution drops the overall fan efficiency by 14%. • A sensitivity analysis of seven fan parameters was carried out. • Comparisons against the predictions of the fan laws were conducted. • The pitch angle is the most influencing parameter on the fan performance. This paper advances a methodology for axial fan efficiency mapping followed by a design optimization exercise of a low-pressure axial fan for small capacity refrigeration applications. For these purposes, a tailor-made first-principles simulation model based on the so-called blade element theory (BET) was put forward. First, the fan efficiency was deployed into two terms – namely, electric motor and blade efficiency, which in turn was split into two other terms that account not only for the irreversible losses but also for flow maldistribution – in order to identify opportunities for blade optimization. Later, a sensitivity analysis was performed to find out the optimum values of key operating and design parameters of the fan, namely motor speed, blade size and number, chord length, pitch angle, and airfoil characteristics, such as thickness and maximum camber values. Among those, the pitch angle stood out as the most influencing parameter affecting the fan characteristics, including the airflow rate, the power consumption, and the blade efficiency. Comparisons with results obtained by means of the so-called fan laws are also reported for the blade size and speed. [ABSTRACT FROM AUTHOR]

Rare earth elements (REEs) are critical materials due to their utilization in high-flux magnets for wind turbines and electric motors. Purification and recycling of REEs are vital for maintaining their supply. This work explores and models nanofiltration (NF) followed by diafiltration for concentrating La3+ and polishing monovalent ions from the concentrated solution. Highly negative monovalent-ion rejections greatly enhance this polishing step, and proton concentrations decrease 3–4 orders of magnitude in 2.4 cell volumes of diafiltration. Studies with rotating membranes give a controlled, uniform boundary layer above the membrane to enable estimation of salt and ion permeances at various feed compositions. Insertion of these permeances in the solution-diffusion-electromigration model yields trends in ion rejections as a function of composition, solution flux, and boundary layer thickness. Simulated rejections of monovalent ions become much more negative with lower solution fluxes (up to a point) and higher ratios of La3+ to monovalent ions. La3+ rejections are much higher in the rotating membrane than in a stirred cell where the diffusion boundary layer is thicker and nonuniform. The combination of NF and diafiltration provides concentrated La3+ with a molar purity of 99 % when starting with equimolar mixtures of La3+ and Na+. Acid removal from La3+ solutions via diafiltration could prove useful for subsequent separations among REEs or other transition metals. [Display omitted] • Diafiltration efficiently polishes La3+ from Na+ or H+ due to negative rejection. • Uniform boundary layers on rotating membranes enable estimation of permeances. • The solution-diffusion-electromigration model gives trends in ion rejections. • Negative monovalent-ion rejections depend on flux, composition, and boundary layers. • Diafiltration yields 99 % La3+ from equimolar Na+ and La3+. [ABSTRACT FROM AUTHOR]

Performance of Lithium Complex (LiX), Polyurea (PU), and Polypropylene (PP) greases in SKF6208 bearings subjected to driving cycle conditions for 28 days (equivalent to 23,000 km of electric vehicle operation) was studied by continuously measuring bearing friction torque and temperature. The energy dissipation was correlated to the differences in oil bleeding and rheology for the three greases. Evolution of the friction torque, friction torque hysteresis, and changes in grease rheology were dominated by the oil release property. The latter was determined by the thickener system and its particular response to the conditions imposed by the driving cycle. A quantitative estimate of the carbon footprint from using these greases to lubricate bearings under driving cycle conditions is also presented. [ABSTRACT FROM AUTHOR]

Increasing the efficiency and sustainability of transportation is a key topic for both automakers and academic researchers. The noise, vibration, and harshness (NVH) of electric and hybrid electric vehicles affect their occupants, which is essential if these vehicles are to be commercially successful. Furthermore, noise pollution in urban areas is a growing concern, and vehicle noise is a major contributor to this problem. Vehicle noise can adversely affect the health and well-being of passengers and pedestrians. A concise, state-of-the-art review of NVH sources and suppression techniques for electric vehicles (EVs), hybrid electric vehicles (HEVs) and internal combustion engine (ICE) vehicles is presented in this paper. NVH is covered for both conventional ICE-powered vehicles as well as electric and hybrid vehicles. Furthermore, the research also addressed NVH sources such as the interior, powertrain, road-tires, suspension, brakes, wind-structure, power-coupling devices, clutches and transmissions, and electric motors. Additionally, the study identifies potential future research areas and NVH sources that need further investigation. By doing so, automobiles will be able to provide a more comfortable ride. According to the study, traditional ICE-powered vehicles' powertrains have a considerable adverse effect on NVH at low speeds. However, NVH resulting from the interaction between the road tire and the wind structure becomes more prominent as the vehicle accelerates. The primary source of NVH in EVs is the power-coupling device, particularly in HEVs. In addition, clutch and transmission noise is present when operating at low speeds with heavy loads. In spite of this, road-tire and wind-structure interactions are the primary sources of NVH at high vehicle speeds, just as they are in conventional ICE-powered vehicles. [ABSTRACT FROM AUTHOR]

This paper studies the viability of energy savings in electric motors by adjusting the voltage according to load in motors that operate under significant load variations during their work cycles. The laboratory test program used a 1.1 kW electric motor to compare its measured efficiency operating without voltage control with the load-based voltage control method results. A neural network was developed, and a time series generator was used to model the motor and estimate the results of applying the method in its useful life in the load behavior of three operating regimes. The results show an energy saving potential of 2 %–5.2 % using the load-based voltage control method in motors operating with a load factor of less than 40 % during the simulated motor life cycle for the three operating regimes. Also, the economic feasibility of implementing the load-based voltage control method was evaluated on three industrial electric motors. Results indicated potential annual savings between $1227 and USD 1,549, with a projected investment payback period of less than three and a half years. • The LVCM is a good solution to save energy in motors with low load factors. • The energy savings potential of the LVCM depends on the operating time at a low load factor. • The lower the load factor, the more energy savings with the LVCM. • The LVCM does not affect the mechanical drive of the electric motor. • Neural networks and time series allow the modeling of LVCM on life cycle motors. [ABSTRACT FROM AUTHOR]

• Sliding mode controller is designed for BLDC motor torque ripple control in EV. • Effectiveness of the controllers is assessed through various time domain analysis. • Effectiveness of the controllers is assessed through motor performance analysis. • Controller efficiency maps are generated in HIL simulation for designed controllers. • Sliding mode controller outperforms other controllers for EV application. Brushless Direct Current (BLDC) motors and their evolution in electric vehicles (EVs) garner attention for their streamlined operation and control methods, enhancing driving range while reducing energy consumption. The primary objective is integrating sliding mode control to enhance BLDC motor capabilities, efficiently regulating speed and torque. The proposed sliding mode (SM) controller mitigates torque ripple and improves dynamic performance amidst fluctuating loads. Speed stabilization and torque control involve comparing reference and predicted speeds, with error feedback integrated into the SM controller. Integrating real-time rules and numerical data with an ANN (Artificial Neural Network)-Fuzzy self-learning algorithm empowers the SM controller to anticipate and mitigate error rates in the BLDC motor, efficaciously modulating motor torque with minimal ripple. Extensive MATLAB/Simulink model-in-loop (MIL) and hardware-in-loop (HIL) simulations demonstrate SM controller superiority over conventional PID, Fuzzy, and PID-Fuzzy controllers, with a rise time of 0.01 s, steady-state error of 0.001 %, settling time of 0.02 s, and peak overshoot of 0.066 %. Moreover, the experiment results show an impressive 29.41 % reduction in torque ripple and the development of efficiency maps to attain the maximum efficiency of 96.12 %. This initiative substantiates that the proposed SM controller to enhance BLDC motor efficiency and EV driving range across real-time conditions. [ABSTRACT FROM AUTHOR]

This article proposes a novel energy management structure for electric vehicles, consisting of a supercapacitor and two types of batteries, to improve efficiency and navigable distance. The key features of a suitable energy storage system include high power and energy density, low cost and weight, minimal maintenance, and long life. Although batteries are the primary power storage source in electric vehicles, they have power limitations. Therefore, a high-power-density supercapacitor is added to the battery to create a hybrid energy storage system, reducing stress on the battery and increasing its lifespan. The article presents a new structure for hybrid storage systems based on the existence of a main battery, a replaceable battery, a supercapacitor, and a DC-DC converter. An active charge equalizer circuit for the main battery in standby mode and its control system are also introduced. A control method for dividing power between different sources under different conditions is presented, and the design parameters of the energy storage system are optimized using a genetic algorithm to minimize mass and losses. The performance of the proposed system is evaluated through simulation in MATLAB software and tested in a small-scale laboratory sample. The article also provides a detailed analysis of different working modes, including electric motor acceleration, low-speed mode, high-speed mode, and electric regenerative braking mode. Additionally, a control method for energy management between batteries and supercapacitors is introduced, aiming to increase efficiency. The results show that the proposed hybrid energy storage system can effectively improve the efficiency of electric vehicles. [ABSTRACT FROM AUTHOR]

With rising concern on environmental protection, the exploitation of EV has been widely focused. The IM is said to be the best in comparing varied electric motors for EV applications due to its lower price and robustness. In addition, sensor-less controlling schemes like DTC and FOC are found to be appropriate for crucial appliances owing to their energy savings, improved efficiency, and reliability. The "Optimized Fractional Order Proportional Integral Controller (FoPID)" with a sensor-less speed estimate mechanism is proposed in this work. Additionally, the parameters of FoPID are adjusted using a brand-new hybrid method called the Wolf based Elephant Herding method (W-EHA), which combines the ideas of Grey wolf optimization (GWO) model and Elephant herding optimization (EHO). The superiority of the recommended technique is finally shown in terms of controller performance and error. The RMSE obtained by the developed model at speed = 100 is 3.344, which is 53.89 %, 24.22 %, 1.09 %, and 38.96 % superior to existing approaches like P-controller, MFI-DA + FoPID, EHO-FoPID, and GWO-FoPID respectively. [ABSTRACT FROM AUTHOR]

[Display omitted] • Zr microalloying improves coercivity and Curie temperature in NdFeB alloys. • Trace Zr addition refines NdFeB grain structure and forms Zr-B phases. • Zr-B phases enhance magnetic stability and mechanical toughness. • Zr-B phases provides grain boundary pinning, aiding crack deflection and bridging. • 0.25–0.40 wt% Zr alloy is promising for electric vehicle motor applications. This study investigated the effects of microalloying (Pr,Nd)FeB alloys with 0.25–0.40 wt% Zr on their mechanical properties and structure. The results demonstrate that the alloys exhibit superior coercivity and operating temperatures compared to those with lower Zr content. The addition of trace amounts of Zr improves the grain structure and forms Zr-B phases during the sintering process. These Zr-B phases provide grain boundary pinning, which aids in crack deflection and bridging, enhancing magnetic stability and mechanical toughness. Such improvements in mechanical properties open new possibilities for designing electric vehicle motors. [ABSTRACT FROM AUTHOR]

Recently, incremental learning (IL) has been widely used in intelligent fault diagnosis of electronic machinery. Most of the typical IL methods have adopted the exemplar-replay strategy to retain the learned diagnostic knowledge. However, it is almost impossible to have infinite storage space to retain fault samples in practical industrial scenarios, which brings a significant challenge for actual industrial applications. To solve this issue, a novel Relationship-Aware Calibrated Prototypical Network (RACPN) is proposed for incremental fault diagnosis of electric motors, which retains learned diagnostic knowledge without requiring the storage of any fault samples from previous sessions. Firstly, a fault prototype calibration (FPC) method is employed to learn new diagnostic knowledge from new sessions. Secondly, a task-relationship representation (TRR), which stands for a method to represent the relationships between tasks, is utilized to enhance the maintenance of diagnostic knowledge across different sessions. Finally, a Gaussian Bayes classifier with Mahalanobis metric is adopted to enhance the inference reliability for classifying fault categories. Experiments conducted on two electrical motor datasets demonstrate the superiority and effectiveness of the proposed RACPN. The results validate that current signals as model input can achieve satisfactory diagnostic performance. The proposed RACPN is a promising tool for incremental fault diagnosis in electric motors. [ABSTRACT FROM AUTHOR]

• Radar-based remote detection of electrical motors' rotational speed is achieved. • The proposed system ensures mobile, non-contact, and safe vibration extraction. • The popular phase extraction methods of radar applications are compared for and applied to electrical machines. Electric motors play a pivotal role in contemporary industrial processes, prompting the necessity for their continuous monitoring through an array of sensors in various applications. Among the crucial parameters under scrutiny, the operational speed of electric motors holds a prominent position. Current methods for speed detection conventionally entail the utilization of physically connected sensors or the measurement of some electrical variables. Nonetheless, a non-contact speed measurement approach with a mobile device promises low cost, efficiency, and even safety in some specific cases. This research delves into the remote speed detection of electric motors employing Continuous Wave radar technology. To this end, phase extraction techniques, which have demonstrated robust performance in diverse application domains, have been assessed for their efficacy in motor speed detection. First, five distinct methods have been utilized to extract the phase of baseband signals obtained from a 24 GHz IQ-demodulated radar system directed toward an asynchronous motor. These methodologies have undergone comprehensive evaluation in experimental measurements and simulation encompassing ideal and noisy conditions. Complex Signal Demodulation, one of the phase extraction methods, exhibits a noteworthy superiority over alternative approaches in motor speed measurement experiments. These experiments have entailed three different load scenarios and encompassed ten distinct speeds, equally spaced between 500 and 1400 rpm. The Complex Signal Demodulation method has delivered exceptional results, successfully detecting motor speeds across thirty experiments with a mean absolute percentage error of merely 0.08. Radar-based non-contact speed detection holds immense promise, particularly in fault diagnosis and predictive maintenance. [ABSTRACT FROM AUTHOR]

Energy depletion and environmental pollution have always been challenges hindering the rapid development of the automotive industry. Electric vehicles (EVs), being promoted worldwide, are expected to bring benefits to energy security and environmental conservation. As one of the key technologies to improve energy efficiency and extend the driving range of EVs, regenerative braking has attracted extensive attention. The aim of this study is to review the configuration, control strategy, and energy-efficiency analysis of regenerative braking systems (RBSs). First, the configuration of RBSs is introduced, including the development of electric motors, friction braking actuators, and energy-storage units, and the application of RBSs to EVs is briefly elaborated. Then, the regenerative braking control strategy is summarized from three perspectives, that is, energy economy under general braking, braking stability under emergency braking, and driving comfort under braking mode switching. Among these, mainly the energy-recovery economy of the regenerative braking control strategy is analyzed. In addition, energy-transfer efficiency is analyzed considering the transmission system efficiency and low-speed working characteristics of electric motors. Finally, the challenges of RBSs in the application of EVs are discussed, which provides insights for future research. • Introduce the current research status of the configuration of regenerative braking systems in electric vehicles. • A review of regenerative braking control strategies for electric vehicles. • Analyze the energy transfer efficiency of the regenerative braking system. • Explore the future development issues and challenges of regenerative braking systems. [ABSTRACT FROM AUTHOR]

Accelerating the development of clean energy technologies is required to move towards a sustainable future. New design approaches are being proposed to help accelerate these developments. This study proposes and improves a novel design framework that incorporates life cycle assessment (LCA) and techno-economic assessment (TEA) with an optimization-based design model of a discrete product at early stage. Objective functions for mass, energy consumption, and two metrics relating to manufacturer and consumer economic interests are considered; these objectives are minimized using a Pareto-like approach. An electric traction motor for an electric vehicle is used as a discrete product case study. The approach demonstrates the utility of considering four-objectives in the design problem, uncertainty analysis via Monte Carlo simulation, and the power of employing LCA and TEA methods. Future work may explore a broader range of objective functions to cover different challenges that inhibit the development of clean energy technologies. [Display omitted] [ABSTRACT FROM AUTHOR]

Electric motors account for over 53% of global electricity consumption, making their energy efficiency relevant for climate change mitigation and for a more competitive industry. However, more efficient motors often require more materials. Despite this, research primarily focuses on motors' energy efficiency during usage, neglecting other life cycle phase like manufacturing and disposal. This study conducted a Systematic Literature Review, identifying 1112 publications on the topic, with only 20 deemed relevant. Squirrel Cage Induction Motors (SCIM) were dominant due to their cost, reliability, and efficiency. However, over the past 30 years, efficiency has improved largely due to altered material use. This impacts production and disposal phases but lessens the use phase impact. Alternatives like Switched Reluctance Motors (SRM) provide better energy efficiency with fewer materials compared to SCIM. Permanent Magnet Synchronous Electric Motors (PMSM) emerge as the most energy efficient but with high environmental impacts in production and disposal. Synchronous Reluctance Motors (SynRM) are competitive SCIM alternatives, boasting less vol/wt, higher efficiency, and reduced impacts. The analyzed Life Cycle Assessments (LCAs) showed variations in included life cycle phases, materials accounted for, and impact categorization. Thus, a tiered framework for electric motor LCAs is recommended. The use phase has the most significant impact, accounting for over 90% of life cycle impacts. Efficient motors generally have reduced environmental effects over their lifespan, even if their production and disposal impacts are higher. Notably, all analyzed LCA publications are European, so findings might vary in other regions. The study concludes by highlighting seven research gaps to further reduce electric motors' environmental impacts. [Display omitted] • The impacts of the use stages of electric motors are predominantly in LCA. • PMSM having the highest impact in the production and disposal phases. • SCIM will gradually be replaced by SynRM, PMSM and SRM. • Novel LCA framework for electric motors proposed. • 7 gaps requiring further research identified. [ABSTRACT FROM AUTHOR]

Traction motor bearings in electric vehicles fail prematurely due to electrical environments. Current flow through the bearings causes lubricant degradation due to a rise in the contact temperature. This study utilizes experimental and numerical methods to predict the expected temperature rise in ball-on-disk contacts subjected to electromechanical loading. Contact resistance and temperature rise are measured using a modified tribo device under static, dynamic, lubricated, and unlubricated conditions. The contact resistance depends on the magnitude of the current applied and contact conditions. A numerical model is proposed to predict the temperature rise at the electromechanical contact and is verified with measured temperatures. Prediction of contact temperatures due to electromechanical loads will assist in life estimation and development of appropriate lubricants. • A methodology to predict temperature rise in electromechanical contact is proposed. • Lubricated contact under EM loading is assessed in the new device developed. • Contact resistance and temperature rise in wear track are reported for EM loading. • The mechanism of current flow in lubricated ball-on-disk contact is discussed. • The simulations predicted a high temperature rise due to electrical loading. [ABSTRACT FROM AUTHOR]

New modeling challenges are accompanying the shift in EU product policy toward an increased focus on circular economy aspects. Combined material flow analysis and life cycle assessment can play an important role in assessing the impact of such policies. A flexible model has been developed that is suitable for the ex-ante impact assessment of the material flows and environmental impacts of a range of circular economy product policies, extending an established approach. The model uses a layered approach, in which material and environmental impacts are derived from product flows via a product database that defines physical properties for product variants. Combined with a stock model, the impact of policy interventions on the whole market can be assessed over time and per life cycle stage. We apply this model in a theoretical case study on electric motors, which compares early replacement of inefficient motors and motor repair with a base case. [Display omitted] [ABSTRACT FROM AUTHOR]

• Transition and latest market share of electrified vehicles in the UK towards decarbonisation legislative targets. • Overview of electric motors construction for transport electrification, and their use of critical materials (CM) • Current REEs market, supply chain constraints, and potential alternative sources via circular economy strategies. • Highlighting the scope for REEs recycling and challenges associated with disassembly of end-of-life (EoL) e-machines. • Critical review of reported e-machine disassembly approaches, and various techniques for REEs recycling. Increasing concerns over climate change have led to global decarbonisation efforts, in the form of new legislation, to phase out the sale of internal combustion engine (ICE) vehicles. As a result, the transition to electrified powertrain vehicles as the mode of transportation has never been greater. Electric motors (EMs), serving as the pivotal component of e-mobility, have gained much attention by policy makers and economic experts concerning the supply chain of raw materials needed for manufacturing. Permanent magnets (PMs), including rare earth elements (REEs), account for 40 to 60 % of the total EM cost. Given the importance of these materials to the e-mobility efforts, there has been a great impetus by leading economies to mitigate supply chain instability and mining operation constraints, by identifying and establishing a sustainable supply source through circular economy strategies. Although extensive studies on REEs recovery, via various techniques, have been undertaken by the research community, there remain underlying concerns over feed source, quality and technical challenges surrounding the retrieval of PM via a functional disassembly approach, all of which are yet to be elucidated. The present study serves to highlight state-of-the-art recycling of EMs from EoL electrified vehicles using a circular economy approach. [ABSTRACT FROM AUTHOR]

• A novel dual piston linear compressor prototype is presented. • The experimental results verify the established numerical model. • Piston operation is a direct control variable, which means the volumetric efficiency can be regulated. • The output characteristics, especially linear motor efficiency, depend heavily on the operating frequency and stroke. A novel dual-piston linear compressor consisting of two piston-cylinder assemblies and a linear electric motor was constructed. To explore the performance of the dual-piston linear compressor, a numerical model that contains a thermodynamic sub-model, dynamic sub-model, three-phase linear motor sub-module, and control system sub-model was built. Several piston trajectories and different operating conditions were assessed to investigate the performance of the dual piston linear compressor. Results from both the simulation and experiments indicate that the system with the triangle curve trajectory exhibits the best performance. The output characteristics (mass flow rate, motor efficiency, mechanical efficiency, and overall efficiency) depend heavily on the operating frequency and the stroke of the piston. For the dual-piston linear compressor system that was designed, the overall efficiency can reach up to 57.59% when the system works at a frequency of 12 Hz and a stroke of 26 mm. [ABSTRACT FROM AUTHOR]

In this paper 1 1 This paper has been modified from the conference paper "Conceptual Design and Optimization of a General Aviation Aircraft with Fuel Cells and Hydrogen", presented at the Aerospace Europe Conference in Bordeaux, France, February 2020. , an aircraft design from scratch and optimization is carried out to investigate the potentials of using liquid hydrogen and fuel cells in general aviation. The focus is set on finding an efficient aircraft configuration that considers all drive train-related components such as the hydrogen tank, fuel cells, and electric motors as well as passenger seats and cargo hold. The paper starts with the definition of the design requirements and specifications. Following, the baseline design of the aircraft in the Suave tool is presented. This includes making extensions to the Suave tool regarding the compatibility of fuel cells and hydrogen energy networks. Eventually, a multidisciplinary design optimization process of selected design variables together with the design constraints is carried out in Suave. Finally, the design is evaluated in terms of performance and emissions by drawing a comparison with conventional general aviation aircraft. • A clean sheet aircraft design using liquid hydrogen and fuel cells is performed. • A tried and tested fuel cell model is added to the SUAVE aircraft design tool. • Design optimization including both the geometry and propulsion system is carried out. • Performance of small hydrogen aircraft is comparable to conventional aircraft. [ABSTRACT FROM AUTHOR]

The problem of building a real-time model for the nonlinear dynamic object is considered. The parameters of the object are unknown in the General case can be treated as time-varying. For control, it is necessary to build an adequate model of this object. The model is built using a recursive neural network. The identification quality criterion is the average loss. Based on observations of the input and output of the object and the configurable model, the identification algorithm changes the parameters so that the average loss reaches a minimum with growth. The results of the analytical construction of the model and the results of modeling based on specially developed software are presented. [ABSTRACT FROM AUTHOR]

• A new active vibration control for motion tracking on DC motors is introduced. • Formulae to compute parameters of unknown harmonic vibrations are proposed. • Amplitude, frequency and phase parameters are estimated online and closed loop. • Online parameter estimation is performed using measurements of the output signal. • Online parameter estimation is extended for a class of controlled dynamic systems. In this article, an active vibration control technique for direct-current electric motors subjected to harmonic mechanical load torque is introduced. Formulae to compute uncertain parameters of amplitude, frequency and phase angle of harmonic torque disturbances for angular velocity reference trajectory tracking are proposed. Vibrating torque disturbances are actively suppressed by the control voltage input. Mathematical modelling based on vibrating systems is adopted for purposes of online parameter estimation of oscillating signals. In this fashion, accurate estimation can be performed using measurements of the output signal only. Online parameter estimation is extended for a class of controllable dynamical engineering systems subjected to harmonic disturbances. Formulae for closed-loop online parameter estimation of harmonic vibrations on differentially flat linear dynamical systems of n degrees of freedom for efficient tracking of desired time-varying motion reference profiles are then presented. Analytical and numerical results prove that proposed formulae can be used to accurately determine the parameters of unknown harmonic vibrations, which is an excellent feature for high-efficiency active vibration control strategies. [ABSTRACT FROM AUTHOR]

This study proposes a modeling and optimization methodology for fuel cell electric vehicles (FCEVs). Among FCEV components, the traction motor, lithium-ion battery, fuel cell stack, and air supply system are mainly investigated. The FCEV modeling is performed based on the vehicle specifications, electromagnetic finite element analysis, and experimental data. To conduct design optimization, deep neural networks (DNNs) are adopted and trained to predict vehicle performance considering the fluctuation of applied direct current voltage. At this stage, the adaptive layering and sampling algorithm was suggested, which enables efficient DNN construction. To confirm the feasibility of the suggested training algorithm, the number of hidden layers and sampling points of constructed DNNs are investigated. Finally, DNN-based fuel economy optimization is performed considering the driving performance. The effectiveness of the proposed optimization methodology is validated by additional optimization results. [Display omitted] • Detailed modeling of the fuel cell electric vehicle was performed. • Wide variation of DC link voltage due to fuel cell characteristics was considered. • Effect of the air supply system on fuel cell performance was reflected. • Adoptive layering and sampling algorithm for deep neural network was suggested. [ABSTRACT FROM AUTHOR]

Improving energy utilization efficiency to extend the range of vehicle is the common issue concerned by various forms of electric vehicles. In order to reveal the influence of electric flywheel and electromechanical flywheel on vehicle economy, two kinds of hybrid energy systems are studied. Firstly, based on the operating characteristics of the two types of flywheels, the topology schemes of the two hybrid energy systems are designed. On this basis, to make full use of the advantages of electric flywheel and electromechanical flywheel, energy management strategies based on wavelet algorithm and logic threshold are designed. Finally, economy tests of the two hybrid energy systems are conducted. Results show that compared with the single energy scheme with lithium battery, under CLTC, as the control motor of the electric flywheel operates under high speed and low torque range frequently, the energy consumption improvement of lithium battery is not enough to compensate for the flywheel energy loss. The net loss of the lithium battery-electric flywheel energy system increases by 2.61%. Profit from efficiency improvement of lithium battery system, increase of regenerative energy recovery and better efficiency of main drive motor, the net loss of the lithium battery-electromechanical flywheel energy system decreases by 6.44%. • A specially structured electromechanical flywheel based on planetary gear set is designed. • An new energy management strategy based on two-stage power split using logic threshold and wavelet is proposed. • The new influences of electric flywheel on lithium battery and composite energy system are discovered. • The special performance influences of electromechanical flywheel on energy power system are reveled. [ABSTRACT FROM AUTHOR]

The current energy management methods for hybrid vehicles are primarily focused on matching the power flow between the engine and the motor. In order to further reduce overall energy consumption and extend the vehicle's lifespan, this paper utilizes model predictive control (MPC) in the energy management of hybrid vehicles to control the energy consumption and temperature of the oil-cooled motor, with a focus on studying the algorithm for solving the optimization problem in MPC. The main work includes: Establishing a simplified model for the oil-cooled motor and training the working condition prediction model based on the worldwide harmonized light vehicles test cycle (WLTC) conditions utilizing long short-term memory (LSTM) recurrent neural network technology. Furthermore, proposing a novel metaheuristic algorithm based on the temporal nature of the problem, multiple hierarchical clustering algorithm (MHCA). In comparison with typical metaheuristic algorithms, the MPC optimized using MHCA exhibits significantly reduced computation time, with an average time of 0.1967s, indicating that using MHCA can theoretically achieve real-time control and eliminate lag in actual control processes. Furthermore, compared to other optimization algorithms, the MHCA algorithm demonstrates the lowest correlation between computation time and operational conditions, highlighting its high robustness in ensuring the safety of practical control. • Built an LSTM-based MPC for energy management on oil-cooled motors in HEV. • Constructed an empirical model for oil-cooled motors. • Proposed a novel metaheuristic algorithm for solving optimization problems in MPC. • The time cost of the algorithm is the lowest among metaheuristic algorithms. • The algorithm showed minimal correlation between runtime and operating conditions. [ABSTRACT FROM AUTHOR]

In the area of automotive propulsion, electric motors experience core losses due to the presence of higher harmonic frequencies, particularly those arising from pulse width modulation switching. Consequently, it is required to establish a practical model capable of characterizing the hysteresis loops in electrical steel when subjected to harmonic excitations. Nonetheless, existing dynamic models may be inappropriate for real-world applications due to their inherent complexity and their tendency to neglect the influence of minor loops arising from harmonics. In the present work, the minor and major hysteresis curves of non-oriented silicon steel sheets are measured under variable frequency excitation containing harmonic components. To reproduce the asymmetrical minor hysteresis loops, a modified arctangent model is employed. The evaluation of the accuracy of this hysteresis model is conducted by comparing the fitted results of static and dynamic hysteresis loops against experimental data, both with and without harmonic excitation. [ABSTRACT FROM AUTHOR]

Predicting the remaining useful lifetime (RUL) of bearings in electric motors is crucial to reduce repair costs in industrial maintenance. With the technological advances of Industry 4.0, physical models for prognostics and RUL prediction have been replaced by data-driven models that require no expert feature extraction. Instead, the model itself learns which features are important. However, these models are normally trained and tested on the same dataset, i.e. under the same operating conditions. This limits the application of a model to other operating conditions unless the model is fine-tuned with data corresponding to those conditions. This paper proposes a novel robust health prognostics technique that detects inner-race bearing failures and predicts the RUL of electric motor bearings under various motor conditions without model retraining or fine-tuning. The model combines time and frequency-domain vibration signal analyses to extract features, a stacked variational denoising autoencoder (SVDAE) to fuse these features and build a Health Indicator and a bidirectional long short-term memory (BiLSTM) neural network to predict the remaining useful lifetime of the bearings. The proposed model is trained with a dataset, validated with another dataset and finally tested with seven additional datasets corresponding to vibrations gathered from different motors and operating conditions. The results are more robust and accurate than those of the literature, the robustness of the prediction with different motor and operating conditions is proven, and there is no need to retrain or fine-tune the model, making the proposed model suitable for recently installed equipment. • Inner-race bearing frequencies are used to predict RUL of electric motor bearings. • SVDAE and BiLSTM help the proposed prediction model improve the literature results. • Random search optimization technique is used for hyperparameter selection of BiLSTM. • Robustness while predicitng is achieved under different motor operating conditions. • Proposed solution can determine the failure apart from predicting the RUL. [ABSTRACT FROM AUTHOR]

With the accelerating electrification revolution, new challenges and opportunities are yet emerging, despite range anxiety is still one of the biggest obstacles. Battery has been in the spotlight for resolving this problem, but other critical vehicle components such as traction motors are the key to efficient propulsion. Traction motor design involves a multidisciplinary approach, with still significant room for improvement in terms of efficiency. Therefore, this paper provides a comprehensive review of scientific literature looking at various aspects of traction motors to maximize mechanical efficiency for the application to high-performance Battery Electric Vehicles. At first, and overview on the mechanical design of electric motors is presented, focusing on topology selection, efficiency, transmission systems, and vehicle layouts; Special attention is then paid to the thermal management, as it is one of the main aspects that affects the global efficiency of such machines; thirdly, the paper presents a discussion on possible future trends to tackle ongoing challenges and to further enhance the performance of traction motors. • Challenges and opportunities to maximize the overall efficiency of traction motors from a mechanical design point of view. • Overview of various types of losses in traction motors with their mathematical formulation and minimization strategies. • State-of-the-art transmission systems used in EVs, and their comparison based on vehicle performance and efficiency. • Driveline configurations to exploit the maximum efficiency and their impact on the vehicle performance. • Thermal Management Schemes pertinent to Mechanical design changes and their influence on overall efficiency. • Material and Additive Manufacturing advances to enhance the overall efficiency of traction motors. [ABSTRACT FROM AUTHOR]

Performance of electric motors and losses in terms of heat and temperature are reviewed in this paper. Airgap eccentricity, electromagnetic performance, effect of temperature and losses are shown as factors affecting the efficiency. Several methods of computer aided analyses are listed. Temperature distribution in an induction motor is shown through the results of a simulation. Different cooling methods are reviewed. Future directions for research include cryogenic cooling, heat pipes and usage of phase change materials. [ABSTRACT FROM AUTHOR]

Outer-rotor PM synchronous motor (OR-PMSM) with PM flux has shown to generate high torque and power densities. However, the round rotor used provides high iron loss and weight that affect their speed. This paper, addresses the problem using 24-stator and 14-segments flux switching machine (FSM) whose rotor is passive. Initially, performances of the designed motor such as cogging torque, harmonic distortion, average torque and power are analyzed. The initial design is optimized and the performances between initial and optimized OR-PMFSM designs are compared. The result shows OR-PMFSM has provided low cogging torque and low odd harmonic distortion to operate safely. The torque has increased to 48.81% from initial to optimize design of 240.5Nm and 469.8Nm. A comparative analysis of other motors for high torque such as OR-PMSM, OR-HEFSM and OR-FEFSM are presented. The proposed motor is capable to perform in high torque and high power conditions for automotive applications. [ABSTRACT FROM AUTHOR]

Electric motors are industrial systems' components widely diffused enabling all productive processes and safety equipment. They are affected by aging effect with a contribution based on the environmental condition on which they work. In order to design efficient maintenance plans, the behaviour of their main components, such as bearings and winding, has to be predicted. Therefore, a model-based methodology is applied aiming at codifying the failure rate of an electric engine, taking into account the thermal aging and relevant environment boundary conditions in which bearings and winding operate. The winding failure mode is coded by means of the Military standard technique while the bearings one is simulated comparing the Military Standard and the Svenska Kullagerfabriken (SKF) techniques. While the former predicts more conservative behaviours, the latter, taking into account lubrication conditions, dynamic loads and a better knowledge of materials quality, enables to capture the evolution of the operative conditions. The proposed reliability model can capture both the deterministic and stochastic behaviour of the electric motor: it belongs to the field of hybrid automaton application; the model is coded by means of the emerging software framework called SHYFTOO. The proposed model and the Monte Carlo simulation process that performs its evolution can support the development of a new class of electric motors: a cyber-physical oriented electric motor. [ABSTRACT FROM AUTHOR]

The paradigm of Industry 4.0 allows to increase the efficiency and effectiveness of the production. Companies that will implement advanced solutions in production systems will increase their level of competitiveness and will be able reach high market shares. The present paper is focused on the development of advanced digital solutions to be implemented on a close power loop test bench designed to test high power transmissions for naval unit. In particular, the test configuration consists of a back-to-back connection between two identical mechanical reducers. Since the efficiency of these systems are very high, it is not necessary to use large electric motors, thus managing to contain the operating costs of the testing phase. The particular test bench allows to size the electric motor simply based on the dissipated power by the kinematic mechanisms. By means of suitable sensors installed on the test bench it is possible to extrapolate countless technical data. The implementation of Industry 4.0 enabling technologies allows to evaluate the increase in efficiency compared to traditional systems in terms of reduction of noise and vibrations, efficiency of lubrication, reduction of consumption, installation and maintenance cost of the entire system. [ABSTRACT FROM AUTHOR]

In this study, Brushless DC (BLDC) motor, which is commonly used as a drive element in the unmanned aerial vehicle (UAV), electric vehicles, and mobile robots today, is powered by hydrogen technologies as environmentally friendly and controlled by a fractional-order PI (FOPI) controller structure. Proton Exchange Membrane (PEM) electrolyzer, PEM Fuel Cell (PEMFC), storage tank, BLDC motor, and motor driver system are modeled and integrated into the Simulink environment in MATLAB. PEM electrolyzer that is energized from the AC grid via the AC/DC converter generates the hydrogen. This generated hydrogen is stored in the storage tank and used by PEMFC to energize to the BLDC motor. The model of the BLDC motor is controlled by using a closed-loop FOPI controller for the variable speed and torque reference values. Parameters of the FOPI are determined by Moth Swarm Algorithm (MSA) optimization method. It is observed from the results that the PEMFC powered FOPI controlled BLDC motor operates stably at high performance for different speed and torque values as expected from the modern drive systems. Furthermore, it is seen that the required energy for the BLDC motor is provided by the PEMFC-PEM electrolyzer system without interruption and the FOPI controlled BLDC motor successfully follows the reference speed values for the different torque values. • PEM electrolyzer, PEMFC and BLDC motor models are integrated in a system. • BLDC motor is controlled by FOPI controller. • DC-DC converter is controlled by FOPI controller. • Parameters of the controller determined by Moth Swarm Algorithm. [ABSTRACT FROM AUTHOR]

• The control algorithm selection of a solar tracker impacts in the tracking accuracy. • The closed-loop control is the most used strategy in solar tracking systems. • The on–off control algorithm is the most used algorithm in solar tracking systems. • Proposal for alternative classification of control algorithms for solar trackers. • IEC 62817 standard is required for the validation of the solar trackers' performance. It is well known that concentrating solar power and concentrating photovoltaic technologies require high accuracy and high precision solar tracking systems in order to achieve greater energy conversion efficiency. The required tracking precision depends primarily on the acceptance angle of the system, which is generally tenths of a degree. Control algorithms applied to active solar tracking systems command and manipulate the electrical signals to the actuators, usually electric motors, with the goal of achieving accurate and precise solar tracking. In addition, a solar tracking algorithms system must provide robustness against disturbances, and it should operate with minimum energy consumption. In this work, a systematic review of the control algorithms implemented in active solar tracking systems is presented. These algorithms are classified according to three solar tracking control strategies: open-loop, closed-loop and combined open- and closed-loop schemes herein called hybrid-loop. Their working principles as well as the main advantages and disadvantages of each strategy are analyzed. It is concluded that the most widely used solar tracking control strategy is closed-loop, representing 54.39% of all the publications consulted. On–off, fuzzy logic, proportional-integral-derivative and proportional-integral are the control algorithms most applied in active solar tracking systems, representing 57.02%, 10.53%, 6.14% and 4.39%, respectively. [ABSTRACT FROM AUTHOR]

Due to the fact that any type of aerospace vessel needs energy, and in the future, this energy must be nuclear and obtained by fusion, not by fission, this paper presents shortly a method by which nuclear fusion can be more easily achieved on an industrial scale. On the other hand, normal aircraft will have to be electrically operated with modern electric motors in the future, which will be able to be energized from modern accumulators which in turn will be charged with energy obtained by burning hydrogen. Hydrogen has the advantage of being obtainable by various methods on an industrial scale, sustainable, and of ensuring economic combustion and without pollution. The paper presents ways to extract hydrogen directly from water, including ones made by the authors of the paper over time, but also the possibility of using nuclear energy extracted by fusion also from hydrogen (its ionic isotopes, deuteron or Triton). Image 1 • Nuclear fusion can be more easily achieved on an industrial scale. • Normal aircraft will have to be electrically operated with modern electric motors. • Accumulators will be charged with energy obtained by burning hydrogen. • Hydrogen ensuring economic combustion without pollution. [ABSTRACT FROM AUTHOR]

Tough driving conditions like hilly areas, slippery roads, rough terrains and high-speed driving dominate the effects of non-linearities present within each component of a vehicle. Such conditions cause the behavior of components like energy sources, power processing blocks and electric traction motors to deviate from their nominal behavior. This research work presents two non-linear control methodologies, one being Lyapunov and Backstepping based controller loops and the other being Synergetic based controller loops for these vehicles. Proposed controller methodologies take into account system's non-linearities ensuring asymptotic stability of the controlled system over a wide operating range. Performance of the proposed controllers is validated in MATLAB/Simulink environment. The simulation model used here is a genuine representation of electric power stage in FC-HEV. The controlled system successfully tracks system parameters to reference values when subjected to driving attributes of European extra urban driving cycle (EUDC). • Power stage modeling of FC–UC–Battery Electric Vehicle has been presented. • Asymptotic stability of the overall system using Lyapunov Stability Theory has been proved. • Simulation results of the proposed controller have been presented in MATLAB SIMULINK. [ABSTRACT FROM AUTHOR]

Traditional optimization-based energy management strategies (EMSs) do not consider the uncertainty of driving cycle induced by the change of traffic conditions, this paper proposes a robust online EMS (ROEMS) for fuel cell hybrid electric vehicles (FCHEV) to handle the uncertain driving cycles. The energy consumption model of the FCHEV is built by considering the power loss of fuel cell, battery, electric motor, and brake. An offline linear programming-based method is proposed to produce the benchmark solution. The ROEMS instantaneously minimizes the equivalent power of fuel cell and battery, where an equivalent efficiency of battery is defined as the efficiency of hydrogen energy transforming to battery energy. To control the state of charge of battery, two control coefficients are introduced to adjust the power of battery in objective function. Another penalty coefficient is used to amend the power of fuel cell, which reduces the load change of fuel cell so as to slow the degradation of fuel cell. The simulation results indicate that ROEMS has good performance in both fuel economy and load change control of fuel cell. The most important advantage of ROEMS is its robustness and adaptivity, because it almost produces the optimal solution without changing the control parameters when driving cycles are changed. • An optimization-based online EMS for FCHEVs is proposed. • A linear programming-based EMS is presented to produce the reference solution. • The load change control of fuel cell slows the degradation of fuel cell stack. • Robustness of the proposed online EMS to uncertain conditions of driving cycles. [ABSTRACT FROM AUTHOR]

• Predicted the Hybrid Vehicle sales situation in Japan until 2030. • Estimated End-of-Life Hybrid Vehicle in Japan until 2030 to a more accurate number. • Investigate Hybrid Vehicle components' exportation situation. • Massive resource is flowing out from Japan due to vehicle and parts' exportation. Hybrid Vehicle (HV) is becoming more and more popular around the world in recent years. Japan is the biggest HV market presently, the sales of HV is actually increasing faster than the government has predicted. Meanwhile, a huge amount of End-of-Life HV will emerge in the future, and since HV consumes more rare metal (cobalt and nickel, etc.,) and non-ferrous metal (aluminum and copper, etc.,) during the manufacturing process comparing to ordinary vehicles, the proper treatment and sufficient resource recycling process is indispensable. However, although Japan government installed End-of-Life HV recycling system, recyclable End-of-Life HV in Japan cannot be grasped due to the massive exportation of secondhand HV to developing countries. Moreover, despite secondhand HV, components from End-of-Life HV such as Nickel-Metal Hydride batteries and electric motors will also be exported to developing countries as used parts. Since resource potential of these components is high and will cause pollution problem in exportation destination without proper recycling treatment, their flow should also be studied. This research aims at estimating recyclable End-of-Life HV number using actual vehicle deregistration rate in Japan while considering secondhand HV exportation trend. Moreover, the flow of previously mentioned components was also studied. Scenario analysis on the secondhand HV exportation and components' flow was further performed, and the effect of secondhand HV and components' exportation was discussed. The result shows that, only 0.11 million waste HV will be recycled in Japan in 2030 under the basic scenario and will not surpass 1 million in all 3 additional scenarios. [ABSTRACT FROM AUTHOR]

Due to the alignment of two easy 〈100〉 axes in the sheet plane, the cube orientation ({001}<100>) is an ideal texture for non-oriented electrical steel sheets used as core lamination for electric motors. However, this magnetically favorable texture was rarely able to be produced using conventional rolling and annealing routes in non-oriented electrical steels. In this research, inclined cold rolling − a simple rolling scheme to alter the initial texture before cold rolling − was applied to a 2.8 wt% Si non-oriented electrical steel, in order to intentionally "create" a rotated Goss ({110}<110>) texture before cold rolling, which was not commonly observed in hot-rolled electrical steels. Plane-strain compression (rolling) of the rotated Goss was able to produce cube crystallites within the matrix, at the grain boundaries and within the shear bands of the deformed rotated Goss grains. The cube crystallites within the shear bands had lower stored energy than their surroundings, and served as the initial seeds for nucleation. Upon annealing, the cube crystallites preferentially nucleated from the shear bands and competitively grew out of the surrounding substructure, forming a strong cube texture in the final sheet. The formation of the initial cube crystallites within the shear bands of the deformed microstructure was believed to be necessary for the development of a final cube texture in the annealed electrical steel sheet. Although inclined rolling may be difficult to be implemented in industrial production, its unique capability to produce uncommon initial texture before cold rolling provides an interesting technique for the study of texture involution during thermomechanical processing. Image, graphical abstract [ABSTRACT FROM AUTHOR]