Search Results (175)

The switched reluctance motors (SRMs) are an attractive solution for electric vehicles (EVs) and hybrid electric vehicles (HEVs). However, the main drawbacks of SRMs are their highly nonlinear magnetic characteristics, complicated control algorithms, and the inherent torque ripples. This paper presents a simple structure average torque control (ATC) technique with a better ability to reduce torque ripples. Based on the detailed analysis of an inductance profile, this paper introduces a novel current compensation mechanism (CCM) that has the ability to profile the phase current and, hence, reduce the torque ripple. The proposed CCM is meant for the minimum inductance zone (MIZ) to profile the current of the ongoing phase. Over the MIZ, the inductance is independent of the phase current that helps to simplify the deduced mathematical formulations and provides a simple structure ATC with a lower computational burden, making it a feasible solution for real-time implementations and future developments. A series of experimental results are achieved to show the feasibility and effectiveness of the proposed ATC technique. The results show the superior performance of the proposed ATC, providing better torque profiles and reducing the torque ripples with an average value of 30% compared to conventional ATC. Full article

Torque motors are typically operated within a limited angular range and are widely used in high-precision control applications due to their ability to provide uniform torque throughout the operating region. In this paper, a new torque motor structure is proposed that enhances torque density while maintaining the inherent torque uniformity. The proposed motor employs an optimized stator pole geometry that enables the magnetic flux generated by both the armature and the permanent magnet to contribute more effectively to torque production. To clarify the torque generation mechanism, the flux distributions of the field and armature were analyzed and validated through finite element analysis. Key design parameters were then defined, and an optimal design was performed to maximize the average torque. The performance of the proposed structure was evaluated through a comparative analysis with a conventional torque motor, confirming its superiority. Finally, a prototype of the proposed torque motor was fabricated, and its torque performance was verified through load testing. Full article

The study analyzed the energy flow of a second-generation Toyota Mirai FCEV under Real Driving Conditions (RDC) in ECO and Normal driving modes. The results demonstrated significant operational differences between the two modes. The ECO mode reduced the maximum motor torque from 286.5 Nm to 187.6 Nm (−51%) but increased the high-voltage (HV) battery State of Charge swing (ΔSOC = 17.26% vs. 10.59%, +63%). Regenerative energy recovery rose by ~19.8% overall and by 25.7% in urban driving. The ECO mode exhibited higher HV battery cycling (4.03 Wh vs. 3.27 Wh) and slightly higher fuel cell energy use in urban conditions (+8.5%). The average fuel cell power was 36% higher in Normal mode, whereas the HV battery output was 11.4% higher in ECO mode. Hydrogen consumption in Normal mode was two times higher in urban and highway phases and three times higher in rural driving compared to ECO mode. In summary, the ECO mode enhances regenerative energy utilization and reduces total onboard energy consumption, at the expense of peak torque and increased battery cycling. These results provide valuable insights for optimizing energy management strategies in fuel cell electric powertrains under real driving conditions. The study introduces an independent methodology for high-resolution (1 Hz) electric energy-flow monitoring and quantification of energy exchange between the fuel cell, high-voltage battery, and powertrain system under Real Driving Conditions (RDC). Unlike manufacturer-derived data or laboratory simulations, the presented approach enables empirical validation of on-board energy management strategies in production FCEVs. The results reveal distinctive energy-flow patterns in ECO and Normal modes, offering reference data for the optimization of future hybrid control algorithms in hydrogen-powered vehicles. Full article

To address the automation of table grape harvesting, a clamping and cutting integrated, four-point flexible end-effector is designed, based on the biological and mechanical characteristics of grapes. The clamping device is validated in regard to force closure requirements using a force spiral. On this basis, a finite element model of the grape pedicel–blade system is established, and dynamic simulations of pedicel cutting are conducted using ANSYS 2021/LS-DYNA. The simulation results indicate that when the pedicel diameter is 10 mm, the maximum shear stress is 1.515 MPa. A kinematic simulation of the clamping device is performed using ADAMS, producing a contact force curve between the end effector’s finger joints and the grape during the clamping process. The simulation results show that the peak contact force of 11 N is lower than the critical rupture force of the grape (24.79 N), satisfying the requirements for flexible, low-damage harvesting. Furthermore, to address the vulnerability of grapes, a contact-force control system is designed, employing a position–speed–torque three-loop control strategy. Pressure sensors integrated into the four clamping fingers provide real-time feedback to adjust the contact force, ensuring precise clamping control. Finally, a physical prototype of the end effector and controller is developed, and harvesting trials are conducted in a vineyard. The harvesting success rate reaches 96.7%, with an average harvesting time of 13.7 s per trial. The grape cluster damage and berry drop rates are 3.2% and 2.8%, respectively, meeting the expected design requirements. Full article

The paper primarily focuses on the control strategy of an electric dump truck equipped with an M100 methanol range extender. In response to the significant adverse impact of the constant power control strategy on the lifespan of power batteries and the large rotational speed fluctuations of range extenders under the power-following control strategy, a constant-speed and variable-torque range extender control strategy based on the rule-based control strategy is proposed. This strategy enables power following within the range of 70 kW to 130 kW and fixed-point operation at 50 kW and 150 kW. Through co-simulation using AVL Cruise and MATLAB R2022b/Simulink, the results indicate that under the China Heavy-duty Commercial Vehicle Test Cycle-Dynamic (CHTC-D), with an average vehicle speed of 23.19 km/h, the constant-speed and variable-torque range extender control strategy achieves a higher methanol saving rate compared to both the constant power control strategy and the power-following control strategy, thereby demonstrating better fuel economy. The methanol consumption per 100 km for the dump truck using the constant power control strategy, the power-following control strategy, and the constant-speed and variable-torque control strategy are 62.89 L, 64.49 L, and 62.53 L, respectively. Compared with the same type of diesel range-extended electric dump truck, its fuel usage cost has a significant advantage. Full article

The rapid accumulation of space debris poses a serious threat to operational spacecraft, with the capture and removal of rapidly tumbling non-cooperative targets being a primary challenge. Non-contact electromagnetic de-tumbling technology is a promising solution due to its enhanced safety. This paper addresses the issue of torque modeling and validation in the electromagnetic de-tumbling process for a specific configuration involving a magnetic dipole and a spherical shell under a symmetrically distributed magnetic field. Based on the principles of electromagnetic induction, an approximate analytical expression for the electromagnetic eddy current torque on a rotating spherical shell within a dipole magnetic field is first derived. A high-fidelity finite element model is then established, which reveals a systematic discrepancy between the initial theoretical model and numerical simulation results. A distance-dependent power-law correction factor is introduced to calibrate the theoretical model, significantly improving its accuracy and reducing the average error to 1.5 percent. Finally, a ground-based experimental platform is designed and implemented. The experimental results demonstrate that the corrected approximate analytical model agrees well with the empirical data, verifying its validity and accuracy under the given conditions and providing a reliable theoretical basis for the design of future space debris de-tumbling controllers. Full article

Toroidal propellers have emerged as a promising substitute for next-generation marine propulsors due to their potential advantages in hydrodynamic efficiency and noise control. This article presents a hydrodynamic analysis of toroidal propellers using a potential-based boundary element method (BEM) that enables rapid computations of complex geometries when compared with computationally demanding viscous simulations. The method predicts the inviscid flow characteristics, forces, and circulation distributions of toroidal propellers and is validated against Reynolds-averaged Navier–Stokes (RANS) simulations under various loading conditions and geometric configurations. The comparison shows that the BEM successfully reproduces the overall thrust and torque trends observed in the viscous simulations, although discrepancies arise due to flow separation and the absence of leading-edge vortices that dominate the suction side dynamics in RANS results. The wake alignment model in the BEM captures the overall trajectories of the shed vortices with good consistency, though its concentrated wake representation occasionally brings the trailing wake substantially close to the rear blade surface, which causes locally low pressures that are not present in RANS where boundary layers prevent direct wake impingement. The BEM was further extended for a parametric study that varied pitch, axial spacing, and lateral angle, showing that pitch variations have the most significant influence on propeller loading and thrust characteristics. Overall, the present work demonstrates that the proposed BEM provides a computationally efficient and physically reasonable framework for predicting the performance of toroidal propellers, especially for early-stage geometric design and optimization. Full article

Vision navigation systems provide significant advantages in agricultural scenarios such as pesticide spraying, weeding, and harvesting by interpreting crop row structures in real-time to establish guidance lines. However, the delay introduced by image processing causes the path and pose information relied upon by the controller to lag behind the actual vehicle state. In this study, a hierarchical delay-compensated cooperative control framework (HDC-CC) was designed to synergize Model Predictive Control (MPC) and Sliding Mode Control (SMC), combining predictive optimization with robust stability enforcement for agricultural navigation. An upper-layer MPC module incorporated a novel delay state observer that compensated for visual latency by forward-predicting vehicle states using a 3-DoF dynamics model, generating optimized front-wheel steering angles under actuator constraints. Concurrently, a lower-layer SMC module ensured dynamic stability by computing additional yaw moments via adaptive sliding surfaces, with torque distribution optimized through quadratic programming. Under varying adhesion conditions tests demonstrated error reductions of 74.72% on high-adhesion road and 56.19% on low-adhesion surfaces. In Gazebo simulations of unstructured farmland environments, the proposed framework achieved an average path tracking error of only 0.091 m. The approach effectively overcame vision-controller mismatches through predictive compensation and hierarchical coordination, providing a robust solution for vision autonomous agricultural machinery navigation in various row-crop operations. Full article

Background/Objective: Major research demonstrates that longitudinal loading affects the vertebral growth and disc wedging in the scoliotic animal models; however, there is a scarcity of research on the effect of torque on the vertebral growth. Comparison of the effect of static and dynamic torque on growth is also lacking. The aims of this study were to assess the morphological, histological, and immunohistochemical changes in caudal vertebrae of rats under controlled, static, and dynamic torque. Methods: Adjacent vertebral bodies of female Sprague-Dawley rats were loaded with a torque for 4 weeks. Six rats received a static torque of 1.25 Nm while 6 additional rats received a dynamic torque (2.4 Nm, 1.0 Hz for 15 min/time, 3 times/week). An additional 6 rats formed the control group and received no torque at all. All the rats were later sacrificed, and the tails for histological analysis, immunocytochemistry, and X-rays were obtained. Results: Among the three groups, there were significant differences in right side disc height and average disc height on the proximal vertebrae space in the coronal plane of the X-ray. There were significant differences in the physeal height between static torque and control, or between dynamic torque and control (p < 0.05). The proliferating cell nuclear antigens were detected with variable percentages in samples among the three physeal zones for all groups. Conclusions: Both static and dynamic torque induced asymmetric reduction in the physis and intervertebral disc, which may help to explain the development and vertebral tethering of scoliosis. Full article

Osseodensification (OD) compacts trabecular bone during implant site preparation rather than removing it, potentially enhancing primary stability versus conventional drilling. This review critically appraised clinical and preclinical evidence for OD’s biological and biomechanical efficacy in implant dentistry. We conducted electronic searches in seven databases (PubMed, Scopus, Web of Science, ScienceDirect, SciELO, LILACS, DOAJ) for the period January 2014 to March 2024. Studies comparing osseodensification with conventional drilling in clinical and large-animal models were included. Primary outcomes were insertion torque, implant stability quotient (ISQ), bone-to-implant contact (BIC), bone area fraction occupancy (BAFO), and complications. Of 75 retrieved records, 38 studies (27 clinical, 11 preclinical) provided analysable data. Based on descriptive averages from the narrative synthesis, osseodensification increased mean insertion torque by around 45% (range 32–59%) and initial ISQ by 3–10 units compared with conventional drilling. These gains permitted immediate loading in 78% of cases and shortened operating time (mean reduction 15–20 min). Animal studies demonstrated 12–28% higher BIC and increased peri-implant bone density at 4–12 weeks. No serious adverse events were recorded. Postoperative morbidity was similar between techniques. The collated evidence indicates that osseodensification significantly improves primary stability and may accelerate healing protocols, particularly in low-density (Misch D3–D4) bone. However, the predominance of short-term data and heterogeneity in surgical parameters limit definitive conclusions. Long-term randomised controlled trials with standardised protocols are needed before universal clinical recommendations can be established. Full article

This paper proposes a novel direct-drive rotary actuator based on a modular five-phase outer-rotor flux-switching permanent magnet (FSPM) machine to overcome the limitations of conventional actuators with gear reducers, such as mechanical complexity and low reliability. The research focused on a synergistic design of a lightweight, high-torque-density motor and a precise control strategy. The methodology involved a structured topology evolution to create a modular stator architecture, followed by finite element analysis-based electromagnetic optimization. To achieve precision control, a multi-vector model predictive current control (MPCC) scheme was developed. This optimization process contributed to a significant performance improvement, increasing the average torque to 13.33 Nm, reducing torque ripple from 9.81% to 2.36% and obtaining a maximum position error under 1 mil. The key result was experimentally validated using an 8 kg inertial load, confirming the actuator’s feasibility for industrial deployment. Full article

Active control of injection quantity during start-up idle optimizes automotive diesel engine starting performance, aligning with low-carbon goals. Conventional methods rely on a calibrated demand torque map adjusted by speed, temperature, and pressure variations, requiring extensive labor for calibration and limiting energy-saving and emission improvements. To address this problem, this paper proposes a transient injection quantity active control method for the start-up process based on the variation characteristics of target speed. Firstly, the target speed variation characteristics of the start-up process are optimized by setting different accelerations. Secondly, a transient injection quantity control strategy for the start-up process is proposed based on the target speed variation characteristics. Finally, the control strategy proposed in this paper was compared with the conventional starting injection quantity control method to verify its effectiveness. The results show that the start-up idle control strategy proposed in this paper reduces the cumulative fuel consumption of the start-up process by 25.9% compared to the conventional control method while maintaining an essentially unchanged start-up time. The emissions of hydrocarbon (HC), carbon monoxide (CO), and nitrogen oxides (NOx) exhibit peak reductions of 12.4%, 32.5%, and 62.9%, respectively, along with average concentration drops of 27.2%, 35.1%, and 41.0%. Speed overshoot decreases by 25%, and fluctuation time shortens by 23.6%. The results indicate that the proposed control method not only avoids complicated calibration work and saves labor and material resources but also effectively improves the starting performance, which is of great significance for the diversified development of automotive power sources. Full article

Multiphase electric drives (EDs) offer important advantages for high-demand applications. However, they require appropriate high-performance control strategies. In this context, finite-control-set model predictive control (FCS-MPC) emerges as a promising strategy, offering a notable flexibility to implement multiobjective regulation schemes. When applied to multiphase EDs, standard FCS-MPC exhibits degraded current quality at low and medium control frequencies. Multivector solutions address this issue by properly combining multiple voltage vectors within a single control period to create the so-called virtual voltage vectors (VVVs). In this way, this approach achieves flux and torque regulation while minimizing current injection into the secondary subspace. For this purpose, the VVV synthesis typically prioritizes active vectors with low contribution in secondary subspaces, avoiding the average deception phenomenon. VVV solutions commonly enable an open-loop regulation of secondary currents. Nevertheless, the absence of closed-loop control in the secondary subspace hinders the compensation of nonlinearities, machine asymmetries, and unbalanced conditions in the ED. Considering this scenario, this work implements a multivector FCS-MPC recovering closed-loop control for the secondary subspace. The capability of the proposal to mitigate secondary current injection and compensate for possible dissymmetries is experimentally evaluated in a six-phase ED. Its performance is compared against a benchmark technique in which secondary current regulation is handled in open-loop mode. The proposed control solution significantly improves in current quality, achieving a reduction in harmonic distortion of 54% at medium speed. Full article

Interior permanent magnet (IPM) synchronous motors have gained widespread adoption in electric vehicles (EVs) owing to their durable rotor configurations, expansive operational speed range, and superior efficiency. Nonetheless, typical IPM motor designs frequently exhibit high torque ripple and constrained torque density. To address these issues, a torque enhancement method is introduced by applying both filleting and notching techniques to the stator core. These techniques help reshape the magnetic field directly at the stator, allowing for more precise control of torque production and torque ripple reduction while keeping the rotor structure unchanged. Design variables of the stator in a 12-slot/8-pole fractional-slot V-shaped IPM motor are optimized using a multi-objective genetic algorithm based on a sensitivity constraint for unidirectional operation. The electromagnetic performance of the motor is analyzed through 2D finite element simulations for both no-load and loaded scenarios. The proposed motor increases average torque by 2.45% and significantly reduces torque ripple by 47.73% compared to the conventional motor. These reflect a significant advancement in torque capability. Furthermore, the efficiency of the proposed motor reaches 93.8%. The findings suggest the potential of the proposed filleting and notching techniques for torque capability improvement in EV applications. Full article

Given the growing need for high-performance operation of 4WID-UGVs, coordinated optimization of trajectory tracking, vehicle stability, and energy efficiency poses a challenge. Existing control strategies often fail to effectively balance these multiple objectives, particularly in integrating energy-saving goals while ensuring precise trajectory following and stable vehicle motion. Thus, a hierarchical control architecture based on Model Predictive Control (MPC) is proposed. The upper-level controller focuses on trajectory tracking accuracy and computes the optimal longitudinal acceleration and additional yaw moment using a receding horizon optimization scheme. The lower-level controller formulates a multi-objective allocation model that integrates vehicle stability, energy consumption, and wheel utilization, translating the upper-level outputs into precise steering angles and torque commands for each wheel. This work innovatively integrates multi-objective optimization more comprehensively within the intelligent vehicle context. To validate the proposed approach, simulation experiments were conducted on S-shaped and circular paths. The results show that the proposed method can keep the average lateral and longitudinal tracking errors at about 0.2 m, while keeping the average efficiency of the wheel hub motor above 85%. This study provides a feasible and effective control strategy for achieving high-performance, energy-saving autonomous driving of distributed drive vehicles. Full article