Search Results (1,363)

Electric motors play a decisive role in electric vehicles by converting electrical energy into mechanical motion across various drivetrain components. However, failures in these motors can interrupt the motor function, with approximately 40% of these failures stemming from bearing issues. Key contributors to bearing degradation include shaft voltage, bearing current, and electric discharge material spalling current, especially in motors powered by inverters or variable frequency drives. This review explores the tribological and vibrational aspects of bearing currents, analyzing their mechanisms and influence on electric motor performance. It addresses the challenges faced by electric vehicles, such as high-speed operation, elevated temperatures, electrical conductivity, and energy efficiency. This study investigates the origins of bearing currents, damage linked to shaft voltage and electric discharge material spalling current, and the effects of lubricant properties on bearing functionality. Moreover, it covers various methods for measuring shaft voltage and bearing current, as well as strategies to alleviate the adverse impacts of bearing currents. This comprehensive analysis aims to shed light on the detrimental effects of bearing currents on the performance and lifespan of electric motors in electric vehicles, emphasizing the importance of tribological considerations for reliable operation and durability. The aim of this study is to address the engineering problem of bearing failure in inverter-fed EV motors by integrating electrical, tribological, and lubrication perspectives. The novelty lies in proposing a conceptual link between lubricant breakdown and damage morphology to guide mitigation strategies. The study tasks include literature review, analysis of bearing current mechanisms and diagnostics, and identification of technological trends. The findings provide insights into lubricant properties and diagnostic approaches that can support industrial solutions. Full article

To enhance the reliability of electric propulsion in electric aircraft and address power interruptions caused by current sensor failures, this study proposes a current sensorless fault-tolerant control strategy for permanent magnet synchronous motors (PMSMs) based on a long short-term memory (LSTM) network. First, a hierarchical architecture is constructed to fuse multi-phase electrical signals in the fault diagnosis layer (sliding mode observer). A symbolic function for the reaching law observer is designed based on Lyapunov theory, in order to generate current predictions for fault diagnosis. Second, when a fault occurs, the system switches to the LSTM reconstruction layer. Finally, gating units are used to model nonlinear dynamics to achieve direct mapping of speed/position to phase current. Verification using a physical prototype shows that the proposed method can complete mode switching within 10 ms after a sensor failure, which is 80% faster than EKF, and its speed error is less than 2.5%, fully meeting the high speed error requirements of electric aircraft propulsion systems (i.e., ≤3%). The current reconstruction RMSE is reduced by more than 50% compared with that of the EKF, which ensures continuous and reliable control while maintaining the stable operation of the motor and realizing rapid switching. The intelligent algorithm and sliding mode control fusion strategy meet the requirements of high real-time performance and provide a highly reliable fault-tolerant scheme for electric aircraft propulsion. Full article

This paper catalogues a series of experiments we conducted to explore how to 3D print a DC electric motor. The individual parts of the electric motor were 3D printed but assembled by hand. First, we focused on a rotor with soft magnetic properties, for which we adopted ProtoPasta^TM, which is a commercial off-the-shelf PLA filament incorporating iron particles. Second, we focused on the stator permanent magnets, which were 3D printed through binder jetting. Third, we focused on the wire coils, for which we adopted a form of laminated object manufacture of copper wire. The chief challenge was in 3D printing the coils, because the winding density is crucial to the performance of the motor. We have demonstrated that DC electric motors can be 3D printed and assembled into a functional system. Although the performance was poor due to the wiring problem, we showed that the other 3D printing processes were consistent with high performance. Nevertheless, we demonstrated the principle of 3D printing electric motors. Full article

Background and Objective: Temperature management is key for reliable operation of permanent magnet synchronous motors (PMSMs). The lumped-parameter thermal network (LPTN) is fast and interpretable but struggles with nonlinear behavior under high power density. We propose OLTEM, a physics-informed deep model that combines LPTN with a thermal neural network (TNN) to improve prediction accuracy while keeping physical meaning. Methods: OLTEM embeds LPTN into a recurrent state-space formulation and learns three parameter sets: thermal conductance, inverse thermal capacitance, and power loss. Two additions are introduced: (i) a state-conditioned squeeze-and-excitation (SC-SE) attention that adapts feature weights using the current temperature state, and (ii) an enhanced power-loss sub-network that uses a deep MLP with SC-SE and non-negativity constraints. The model is trained and evaluated on the public Electric Motor Temperature dataset (Paderborn University/Kaggle). Performance is measured by mean squared error (MSE) and maximum absolute error across permanent-magnet, stator-yoke, stator-tooth, and stator-winding temperatures. Results: OLTEM tracks fast thermal transients and yields lower MSE than both the baseline TNN and a CNN–RNN model for all four components. On a held-out generalization set, MSE remains below 4.0 °C² and the maximum absolute error is about 4.3–8.2 °C. Ablation shows that removing either SC-SE or the enhanced power-loss module degrades accuracy, confirming their complementary roles. Conclusions: By combining physics with learned attention and loss modeling, OLTEM improves PMSM temperature prediction while preserving interpretability. This approach can support motor thermal design and control; future work will study transfer to other machines and further reduce short-term errors during abrupt operating changes. Full article

Spinal cord injury (SCI) is a major disability that, to this day, does not have a permanent cure. The spinal cord extends caudally through the body structure of the vertebral column and is part of the central nervous system (CNS). The spinal cord enables neural communication and motor coordination, so injuries can disrupt sensation, movement, and autonomic functions. Mechanical and traumatic damage to the spinal cord causes lesions to the nerves, resulting in the disruption of relayed messages to the extremities. Various forms of treatment for the spinal cord include functional electrical stimulation (FES), epidural electrical stimulation (EES), ‘SMART’ devices, exoskeleton and robotic systems, transcranial magnetic stimulation, and neuroprostheses using AI for the brain–computer interface. This research is going to analyse and review these current treatment methods for spinal cord injury and identify the current gaps and limitations in these, such as long-term biocompatibility, wireless adaptability, cost, regulatory barriers, and risk of surgery. Future advancements should work on implementing wireless data logging with AI algorithms to increase SCI device adaptability, as well as maintaining regulatory and health system integration. Full article

As the range of applications for amphibious robots expands, higher demands are being placed on their working time and working range. This paper proposed a power supply system for an amphibious robot based on wave energy generation, which can convert wave energy into electric energy to enhance endurance. First, the no-load induced electromotive force, magnetic line distribution vector diagrams, and magnetic density cloud diagrams of the cylindrical and flat generators were compared by finite element simulation, which determined that the cylindrical structure has better power generation performance. Then, the electromagnetic parameters of the cylindrical generator were analyzed using Ansys Maxwell, and the final dimensions were determined. Finally, the wave motion was simulated using a swing motor, and the effects of different cutting speeds for the actuator before and after rectification, as well as series-parallel capacitance on the power generation performance of the designed generator, were experimentally analyzed. This provides a potential solution to enhance the working time and working range of amphibious robots. Full article

Aiming at the multifunctional requirements of the limited space in high-end vehicle side-door latches, a double single-loop RRUPRR mechanism driven by a single motor for both electric releasing and cinching is proposed based on the POC set. The kinematical equations of the RRURR mechanism possess 2 × 2 analytical solutions. In order to apply the current motion/force transmission performance index of the parallel mechanisms to the transmission performance analysis of the serial mechanisms, matching methods for chain-driving transference and the moving/fixed platform inversion are proposed. The solution of the performance index of a single-degree-of-freedom single-loop mechanism is equivalent to the solution of the input motion/force transmission performance index of a parallel mechanism. The overall motion/force transmission performance index of a single-loop mechanism is constructed, and the corresponding calculation procedure is defined. Chain-driving transference can be obtained through forward and inverse solutions of the RRURR mechanism. In response to the extremely high requirements for motion/force transmission performance of electric release mechanisms, the proposed overall motion/force transmission performance index is used to calculate for the input motion screw and corresponding transmission-force screw of the single-loop RRURR mechanism and obtain the overall motion/force transmission performance of the mechanism. The performance atlas of the mechanism shows that it has excellent motion/force transmission characteristics within the workspace. Using ADAMS simulation software, the driving torque required for electric releasing and cinching of a vehicle side-door latch mechanism with a single motor is analyzed. The overall motion/force transmission performance index of a single-loop mechanism can be applied to single-loop overconstrained mechanisms and non-overconstrained mechanisms. Full article

Brain–computer interface (BCI) technology holds promise for improving motor rehabilitation in stroke patients. This review explores the immediate and long-term effects of BCI training, shedding light on the potential benefits and challenges. Clinical studies have demonstrated that BCIs yield significant immediate improvements in motor functions following stroke. Patients can engage in BCI training safely, making it a viable option for rehabilitation. Evidence from single-group studies consistently supports the effectiveness of BCIs in enhancing patients’ performance. Despite these promising findings, the evidence regarding long-term effects remains less robust. Further studies are needed to determine whether BCI-induced changes are permanent or only last for short durations. While evaluating the outcomes of BCI, one must consider that different BCI training protocols may influence functional recovery. The characteristics of some of the paradigms that we discuss are motor imagery-based BCIs, movement-attempt-based BCIs, and brain-rhythm-based BCIs. Finally, we examine studies suggesting that integrating BCIs with other devices, such as those used for functional electrical stimulation, has the potential to enhance recovery outcomes. We conclude that, while BCIs offer immediate benefits for stroke rehabilitation, addressing long-term effects and optimizing clinical implementation remain critical areas for further investigation. Full article

The electrification of road vehicles is a relatively mature sector, while other areas of mobility, such as construction machinery, are just beginning their transition to electric solutions. This work presents the design and realization of an integrated drive system specifically developed for retrofitting fan drives in heavy machinery, like bulldozers and tractors, utilizing existing 48 VDC batteries. By replacing or complementing internal combustion and hydraulic technologies with electric solutions, significant advantages in efficiency, reduced environmental impact, and versatility can be achieved. Focusing on the fan drive system addresses the critical challenge of thermal management in high ambient temperatures and harsh environments, particularly given the high current requirements for $3\mathrm{k}\mathrm{W}$-class applications. A sensorless architecture has been selected to enhance reliability by eliminating mechanical position sensors. The developed fan drive has been extensively tested both on a braking bench and in real-world applications, demonstrating its effectiveness and robustness. Future work will extend this prototype to electrify additional onboard hydraulic motors in these machines, further advancing the electrification of heavy-duty equipment and improving overall efficiency and environmental impact. Full article

Electric submersible pumps (ESPs) are critical for artificial lift operations; however, they are prone to frequent failures, often resulting in high operational costs and production downtime. Traditional ESP failure classifications are limited by lack of standardization and the conflation of failure modes with root causes. To address these limitations, this study proposes a new two-step integrated failure modes and root cause (IFMRC) classification system. The new framework clearly distinguishes between failure modes and root causes, providing a systematic, structured approach that enhances fault diagnosis and failure analysis and can lead to better failure prevention strategies. This methodology was validated using a case study of over 4000 ESP installations. The data came from Egypt’s Western Desert, covering a decade of operational data. The sources included ESP databases, workover records, and detailed failure investigation (DIFA) reports. The failure modes were categorized into electrical, mechanical, hydraulic, chemical, and operational types, while root causes were linked to environmental, design, operational, and equipment factors. Statistical analysis, in this case study, revealed that motor short circuits, low flow conditions, and cable short circuits were the most frequent failure modes, with excessive heat, scale deposition, and electrical grounding faults being the dominant root causes. This study underscores the importance of accurate root cause failure classification, robust data acquisition, and expanded failure diagnostics to improve ESP reliability. The proposed IFMRC framework addresses limitations in conventional taxonomies and facilitates ongoing enhancement of ESP design, operation, and maintenance in complex field conditions. Full article

Blind and visually impaired (BVI) people face significant challenges in perception, navigation, and safety during travel. Existing infrastructure (e.g., blind lanes) and traditional aids (e.g., walking sticks, basic audio feedback) provide limited flexibility and interactivity for complex environments. To solve this problem, we propose a real-time travel assistance system based on deep learning. The hardware comprises an NVIDIA Jetson Nano controller, an Intel D435i depth camera for environmental sensing, and SG90 servo motors for feedback. To address embedded device computational constraints, we developed a lightweight object detection and segmentation algorithm. Key innovations include a multi-scale attention feature extraction backbone, a dual-stream fusion module incorporating the Mamba architecture, and adaptive context-aware detection/segmentation heads. This design ensures high computational efficiency and real-time performance. The system workflow is as follows: (1) the D435i captures real-time environmental data; (2) the processor analyzes this data, converting obstacle distances and path deviations into electrical signals; (3) servo motors deliver vibratory feedback for guidance and alerts. Preliminary tests confirm that the system can effectively detect obstacles and correct path deviations in real time, suggesting its potential to assist BVI users. However, as this is a work in progress, comprehensive field trials with BVI participants are required to fully validate its efficacy. Full article

This paper proposes an anti-disturbance model predictive fault-tolerance control strategy for open-circuit faults of five-phase flux intensifying fault-tolerant interior permanent magnet (FIFT-IPM) motors. This strategy is applicable to electric agricultural equipment that has an open winding failure. Due to the rich third-harmonic back electromotive force (EMF) content of five-phase FIFT-IPM motors, the existing model predictive current fault-tolerant control algorithms fail to effectively track fundamental and third-harmonic currents. This results in high harmonic distortion in the phase current. Hence, this paper innovatively proposes a multi-plane virtual vector model predictive fault-tolerant control strategy that can achieve rapid and effective control of both the fundamental and harmonic planes while ensuring good dynamic stability performance. Additionally, considering that electric agricultural equipment is usually in a multi-disturbance working environment, this paper introduces an adaptive gain sliding-mode disturbance observer. This observer estimates complex disturbances and feeds them back into the control system, which possesses good resistance to complex disturbances. Finally, the feasibility and effectiveness of the proposed control strategy are verified by experimental results. Full article

The electromechanical composite transmission technology for tracked vehicles demonstrates excellent performance in energy efficiency, mobility, and ride comfort. However, due to frequent operation under harsh conditions, the components of the electric drive system, such as drive motors, are prone to failures. This paper proposes three fault-tolerant control methods for three typical fault scenarios of the electromechanical composite transmission system (ECTS) to ensure the normal operation of tracked vehicles. Firstly, an ECTS and the electromechanical coupling dynamics model of the tracked vehicle are established. Moreover, a double-layer anti-windup PID control for motors and an instantaneous optimal control strategy for the engine are proposed in the fault-free case. Secondly, an anti-windup PID control law for motors and an engine control strategy considering the state of charge (SOC) and driving demands are developed in the case of single-side drive motor failure. Thirdly, a B4 clutch control strategy during starting and a steering brake control strategy are proposed in the case of electric drive system failure. Finally, in the straight-driving condition of the tracked vehicle, the throttle opening is set as 0.6, and the motor failure is triggered at 15 s during the acceleration process. Numerical simulations verify the fault-tolerant control strategies’ feasibility, using the tracked vehicle’s maximum speed and acceleration at 30 s as indicators for dynamic performance evaluation. The simulation results show that under single-motor fault, its straight-line driving power drops by 33.37%; with electric drive failure, the drop reaches 43.86%. The vehicle can still maintain normal straight-line driving and steering under fault conditions. Full article

There has been a great need for replacing combustion-powered vehicles with electric vehicles (EV), and fully electric cars are meant to replace combustion engine cars. This has led to considerable research into improving the performance of EVs, especially via electric motor voltage control. A wide range of optimization algorithms have been used as traditional approaches, but the dynamic parameters of electric motors, impacted by temperature and different driving cycles, continue to be a problem. This study introduces an improved version of the Parrot Optimizer (IPO) aimed at enhancing voltage regulation in EVs. The algorithm can intelligently adjust certain motor parameters for adaptive management to maintain performance based on different situations. To ensure a stable and sustainable power supply for the powertrain of the EV, a photovoltaic (PV) system is used with energy storage batteries. Such an arrangement seeks to deliver permanent electric energy, a solution to traditional grid electricity reliance. This demonstrates the effectiveness of IPO, with the resultant motor performance remaining optimal despite parameter changes. It is also illustrated that energy production, by integrating PV systems, prevents excessive voltage line drops and thus voltage imbalances. The proposed intelligent controller is verified based on multiple simulations, demonstrating and ensuring significant improvements in EV efficiency and reliability. Full article

In recent years, the rapid spread of electric vehicles (EVs) has intensified the competition to develop power units for EVs. In particular, improving the driving range of EVs has become a major topic, and in order to achieve this, many studies have been conducted on improving the efficiency of EV power units. In this study, we propose a multiple-inverter-drive permanent magnet synchronous motor based on an 8-pole, 48-slot structure, which is commonly used as an EV motor. The proposed motor is composed of two completely independent parallel inverters and windings, and intermittent operation is possible; that is, only one inverter and one parallel winding is used depending on the situation. In the proposed motor, we compare losses including stator iron loss, rotor iron loss, and magnet eddy current loss by PWM voltage inputs for some stator winding topologies, we show that the one-side winding arrangement is the most efficient during intermittent operation, and that it is more efficient than normal operation especially in the low-speed, low-torque range. Finally, through a vehicle-driving simulation considering the efficiency map including motor loss and inverter loss, we show that the intentional use of intermittent operation can improve electrical energy consumption. Full article