Search Results (265)

To address the challenges of enhancing driving stability and energy efficiency in distributed-drive electric vehicles, this paper proposes an extenics coordinated torque distribution control method that integrates energy efficiency optimization and vehicle stability. The primary contribution was the development of a vehicle stability assessment method grounded in extenics control theory, which was used to obtain the vehicle’s phase plane and stability region. Subsequently, an objective function with constraints for in-wheel motor torque distribution was formulated, targeting both optimal energy efficiency and maximum tire stability margin. Furthermore, the extension distances from the actual vehicle state to the stability boundaries were computed to determine adaptive weighting coefficients for these dual objectives. Finally, a Matlab/Simulink 2018a and Carsim2019 co-simulation platform was built to implement and test the proposed method. Simulations under the NEDC urban driving cycle and double-lane-change driving conditions were conducted to evaluate the following three distribution strategies: energy-optimal, stability-oriented, and extenics coordinated control. The results demonstrated that, regarding vehicle stability performance, extenics coordinated control showed a slightly inferior performance to the stability-oriented approach but substantially outperformed the energy-optimal strategy. In terms of energy consumption, the energy-optimal strategy achieved the lowest loss and the stability-oriented strategy showed the highest, while the extenics coordinated control presented intermediate results of 5.4 × 10⁹ J and 9.7 × 10⁷ J, respectively, under two driving conditions, representing reductions of 2.17% and 11.2% compared to the stability-oriented method. The proposed torque distribution method establishes an effective balance between energy-optimal and stability-oriented objectives. This method not only ensures satisfactory driving stability, but also reduces energy loss in in-wheel motors. Full article

Inter-turn short-circuit (ITSC) faults in motor drives can induce substantial circulating currents and localized thermal stress, ultimately degrading winding insulation and compromising torque stability. To enhance the operational reliability of open-winding (OW) five-phase fault-tolerant fractional-slot concentrated-winding interior permanent-magnet (FTFSCW-IPM) motor drive systems, this paper proposes a real-time fault-tolerant control strategy that provides current suppression and torque stabilization under ITSC conditions. Upon fault detection, the affected phase is actively isolated and connected to an external dissipative resistor, thereby limiting the fault-phase current and inhibiting further propagation of insulation damage. This reconfiguration allows the drive system to uniformly accommodate both open-circuit (OC) and ITSC scenarios without modification of the underlying control architecture. For OC operation, an equal-amplitude modulation scheme based on carrier-based pulse-width modulation (CPWM) is formulated to preserve the required magnetomotive-force distribution. Under ITSC conditions, a feedforward compensation mechanism is introduced to counteract the disturbance generated by the short-circuit loop. A principal contribution of this work is the derivation of a compensation term that can be estimated online using zero-sequence voltage (ZSV) together with measured phase currents, enabling accurate adaptation across varying ITSC severities. Simulation and experimental results demonstrate that the proposed method effectively suppresses fault-phase current, maintains near-sinusoidal current waveforms in the remaining healthy phases, and stabilizes torque production over a wide range of fault and load conditions. Full article

To address the issue of limited accuracy in vehicle lateral and longitudinal dynamics control—caused by the strong coupling and nonlinearity between the four-wheel steering and distributed drive systems, particularly under crosswind disturbances—a control method integrating differential geometric decoupling with robust control is proposed. This integrated approach mitigates coupling effects among the vehicle motions in various directions, thereby enhancing overall robustness. The control architecture adopts a hierarchical structure: the upper layer takes the deviation between the ideal and actual models as input and generates longitudinal, yaw, and lateral control laws via robust control; the middle layer employs differential geometric methods to decouple the nonlinear system, deriving the total driver-required driving torque, additional yaw moment, and rear-wheel steering angle; and the lower layer utilizes a quadratic programming algorithm to optimize the distribution of driving torque across the four wheels. Finally, simulation verification is conducted based on a co-simulation platform using TruckSim 2022 and MATLAB R2024a/Simulink. The simulation results demonstrate that, compared to the sliding mode control (SMC) and the uncontrolled scenario, the proposed method improves the driving stability and safety of the four-wheel steering distributed drive vehicle under multiple operating conditions. Full article

The Switched Reluctance Motor (SRM) is a strong candidate for high-performance industrial drives and electric vehicle (EV) propulsion due to its robust, magnet-free construction and high fault tolerance. However, its main drawback lies in its nonlinear behavior, which produces significant torque ripple and acoustic noise, thereby hindering its widespread adoption. In recent years, Finite Control Set Model Predictive Control (FCS-MPC) has emerged as a promising alternative to mitigate these issues. Nevertheless, existing implementations typically rely on an eight-vector set comprising both single-phase and dual-phase excitations with unequal magnitudes, resulting in a nonuniform distribution in the αβ-plane. Unlike the conventional square-shaped distribution of vectors where excitation alternates between one and two phases, this study proposes a novel vector set that consistently energizes two phases in each selection. This approach achieves a uniform circular distribution in the αβ-plane, enabling the voltage magnitude to remain constant. The proposed eight-vector set leads to smoother current transitions, reduced torque ripple, and improved dynamic behavior. The strategy is validated on the MATLAB/Simulink platform, with detailed comparative results presented against the conventional method. The findings demonstrate a torque ripple reduction of up to 58% and an acceleration time improvement of up to 64%. These results highlight the strong potential of the proposed method for scalable SRM performance enhancement in demanding applications such as EV propulsion systems. Full article

Magnetically controlled spinal growing rods, used for treating early-onset scoliosis (EOS), face a critical clinical limitation: insufficient distraction force. Compounding this issue is the inherent inability to directly monitor the mechanical output of such implants in vivo, which challenges their safety and efficacy. To overcome these limitations, optimizing the rotor’s maximum torque is essential. Furthermore, defining the “continuous rotation domain” establishes a vital safety boundary for stable operation, preventing loss of synchronization and loss of control, thus safeguarding the efficacy of future clinical control strategies. In this study, a transient finite element magnetic field simulation model of a circumferentially distributed permanent magnet–rotor system was established using ANSYS Maxwell (2024). The effects of the clamp angle between the driving magnets and the rotor, the number of pole pairs, the rotor’s outer diameter, and the rotational speed of the driving magnets on the rotor’s maximum torque were systematically analyzed, and the optimized continuous rotation domain of the rotor was determined. The results indicated that when the clamp angle was set at 120°, the number of pole pairs was one, the rotor outer diameter was 8 mm, the rotor achieved its maximum torque and exhibited the largest continuous rotation domain, while the rotational speed of the driving magnets had no effect on maximum torque. Following optimization, the maximum torque of the simulation increased by 201% compared with the pre-optimization condition, and the continuous rotation domain was significantly enlarged. To validate the simulation, a rotor torque measurement setup incorporating a torque sensor was constructed. Experimental results showed that the maximum torque improved from 30 N·mm before optimization to 90 N·mm after optimization, while the driving magnets maintained stable rotation throughout the process. Furthermore, a spinal growing rod test platform equipped with a pressure sensor was developed to evaluate actuator performance and measure the maximum distraction force. The optimized growing rod achieved a peak distraction force of 413 N, nearly double that of the commercial MAGEC system, which reached only 208 N. The simulation and experimental methodologies established in this study not only optimizes the device’s performance but also provides a viable pathway for in vivo performance prediction and monitoring, addressing a critical need in smart implantable technology. Full article

To resolve the inherent coupling conflict between trajectory tracking and lateral stability in distributed electric drive buses, this paper proposes a hierarchical cooperative control framework. A simplified two-degree-of-freedom (2-DOF) vehicle model is first established, and kinematically derived reference states for stable motion are computed. At the upper level, a model predictive controller (MPC) generates real-time steering commands while explicitly minimizing lateral tracking error. At the lower level, a proportional integral derivative (PID)-based roll moment controller and a linear quadratic regulator (LQR)-based direct yaw moment controller are designed, with four-wheel torque distribution achieved via quadratic programming subject to friction circle and vertical load constraints. Co-simulation results using TruckSim and MATLAB/Simulink demonstrate that, during high-speed single-lane-change maneuvers, peak lateral error is reduced by 11.59–18.09%, and root-mean-square (RMS) error by 8.67–14.77%. Under medium-speed double-lane-change conditions, corresponding reductions of 3.85–12.16% and 4.48–11.33% are achieved, respectively. These results fully validate the effectiveness of the proposed strategy. Compared with the existing MPC–direct yaw moment control (DYC) decoupled control framework, the coordinated control strategy proposed in this paper achieves the optimal trade-off between trajectory tracking and lateral stability while maintaining the quadratic programming solution delay below 0.5 milliseconds. Full article

To improve the adaptability of 4WID electric vehicles under various operating conditions, this study introduces a model predictive control approach utilizing a neural network for adaptive weight parameter prediction, which integrates four-wheel steering and longitudinal driving force control. To address the difficulty in adjusting the MPC weight parameters, the neural network undergoes offline training, and the Snake Optimization method is used to iteratively optimize the controller parameters under diverse driving conditions. To further enhance vehicle stability, the real-time stability state of the vehicle is assessed using the $\beta -\dot{\beta }$ phase plane method. The influence of vehicle speed and road adhesion on the instability boundary of the phase plane is comprehensively considered to design a stability controller based on different instability degree zones. This includes an integral sliding mode controller that accounts for both vehicle tracking capability and stability, as well as a PID controller, which calculates the additional yaw moment based on the degree of instability. Finally, an optimal distribution control algorithm coordinates the longitudinal driving torque and direct yaw moment while also considering the vehicle’s understeering characteristics in determining the torque distribution for each wheel. The simulation results show that under various operating conditions, the proposed control strategy achieves smaller tracking errors and more concentrated phase trajectories compared to traditional controllers, thereby improving path tracking precision, vehicle stability, and adaptability to varying conditions. Full article

One of the key issues in vehicle sustainability is their energy efficiency. The article concerns the complex issue of predicting the tractive efficiency of heavy off-road vehicles depending on the parameters of the transfer case. As part of the research, a mathematical model of an off-road truck with simplified drive system was developed and implemented in MATLAB/Simulink environment. Multiple simulations for various parameters were performed. Based on the simulation results, efficiency maps were plotted depending on parameters such as the friction coefficient in the differential mechanism, torque bias of the differential, load distribution and drawbar pull of the vehicle. The results showed that the vehicle generally achieves the highest traction efficiency with the differential operating in locked condition and confirmed that the optimal torque bias is close to the load ratio. However, taking into account the multipass effect shifts this value towards the front wheel, while taking into account the bulldozing effect shifts it towards the rear wheel. Simulated vehicle showed higher efficiency when heavily loaded at higher differential friction, while when lightly loaded, higher efficiency at lower friction. Thanks to its high degree of parameterization, this model can be used to help optimize the drive train of off-road vehicles traveling in various terrains from the energy consumption point of view, leading to more sustainable operation. Full article

To address the issue of poor yaw stability in distributed-drive electric pickup trucks at medium-to-high speeds, particularly under the influence of continuously varying tire forces and road adhesion coefficients, a novel Kalman filter-based method for estimating the road adhesion coefficient, combined with a Tube-based Model Predictive Control (Tube-MPC) algorithm, is proposed. This integrated approach enables real-time estimation of the dynamically changing road adhesion coefficient while simultaneously ensuring vehicle yaw stability is maintained under rapid response requirements. The developed hierarchical yaw stability control architecture for distributed-drive electric pickup trucks employs a square root cubature Kalman filter (SRCKF) in its upper layer for accurate road adhesion coefficient estimation; this estimated coefficient is subsequently fed into the intermediate layer’s corrective yaw moment solver where Tube-based Model Predictive Control (Tube-MPC) tracks desired sideslip angle and yaw rate trajectories to derive the stability-critical corrective yaw moment, while the lower layer utilizes a quadratic programming (QP) algorithm for precise four-wheel torque distribution. The proposed control strategy was verified through co-simulation using Simulink and Carsim, with results demonstrating that, compared to conventional MPC and PID algorithms, it significantly improves both the driving stability and control responsiveness of distributed-drive electric pickup trucks under medium- to high-speed conditions. Full article

In the V-cycle of distributed electric wheel loaders (DEWLs), transport accounts for about 70% of the cycle, making energy saving urgent, while shovel-stage slip limits traction stability. This paper proposes a two-module control framework: (i) a preferred-motor transport strategy that reduces parasitic losses and concentrates operation in high-efficiency regions; and (ii) a load-ratio-based front–rear torque distribution for shoveling that allocates tractive effort according to instantaneous axle vertical loads so that each axle’s torque respects its available adhesion. For observability, we deploy a pre-calibrated lookup-table (LUT) mapping from bucket cylinder pressure to the front-axle load ratio, derived offline from a back-propagation neural network (BP-NN) fit. Tests on a newly developed DEWL show that, compared with dual-motor fixed-ratio control, transport-stage mechanical and electrical power drop by 18–37%, and drive-system efficiency rises by 6–13%. During shoveling, the strategy reduces the peak inter-axle slip from 22–35% to 13–15% and lowers the mean slip to 2.6–5.9%, suppressing sawtooth-like wheel-speed oscillations without sacrificing peak capacity. The method reduces parasitic energy flow, improves traction utilization, and is readily deployable. Full article

Tire contact imprint characteristics and pressure distribution directly affect their lateral mechanical characteristics under rolling conditions, which are the key influencing factors for vehicle handling stability. Based on the nonlinear finite element method, an explicit dynamic model of radial tires is established using Abaqus, and its contact process is simulated through phased load transfer and kinematic inversion. The modified mathematical model of contact pressure distribution is introduced from the geometric evolution law of contact imprint and the nonlinear characteristics of contact pressure distribution. The corrected lateral force and aligning torque and contact imprint behavior are analyzed. The results show that in the low roll-angle range, with the increase in the roll angle, the contact imprint shrinks asymmetrically, the pressure center shifts to the outer shoulder of the roll direction, and the lateral force and aligning torque show linear growth characteristics. At the critical value ±8°, the growth rate is significantly slowed down due to the stress saturation effect of the shoulder area. The research analyzes the evolution mechanism of the lateral mechanical characteristics of the contact imprint geometry and pressure distribution drive tires under roll conditions, providing theoretical support for vehicle handling stability optimization and tire structure design. Full article

In this paper, the concept of symmetry is utilized to design active fault tolerant trajectory-tracking control of autonomous distributed-drive electric vehicles—that is, the construction and the solution of active fault tolerant trajectory-tracking controllers are symmetrical. This paper presents a hierarchical fault tolerant control strategy for improving the trajectory-tracking performance of autonomous distributed-drive electric vehicles (ADDEVs) under steer-by-wire (SBW) system failures. Since ADDEV trajectory dynamics are inherently affected by complex traffic conditions, various driving maneuvers, and other road environments, the main control objective is to deal with the ADDEV trajectory-tracking control challenges of system uncertainties, SBW failures, and external disturbance. First, the differential steering dynamics model incorporating a 3-DOF coupled system and stability criteria based on the phase–plane method is established to characterize autonomous vehicle motion during SBW failures. Then, by integrating cascade active disturbance rejection control (ADRC) with Karush–Kuhn–Tucker (KKT)-based torque allocation, the active fault tolerant control framework of trajectory tracking and lateral stability challenges caused by SBW actuator malfunctions and steering lockup is addressed. The upper-layer ADRC employs an extended state observer (ESO) to estimate and compensate against uncertainties and disturbances, while the lower-layer utilizes KKT conditions to optimize four-wheel torque distribution to compensate for SBW failures. Simulations validate the effectiveness of the controller with serpentine and double-lane-change maneuvers in the co-simulation platform MATLAB/Simulink-Carsim^® (2019). Full article

Hydraulic motors are increasingly pivotal in high-power drive systems for heavy-duty vehicles and industrial machinery due to their high power density. Radial piston hydraulic motors are commonly employed in heavy-load applications, while digital hydraulic motors have surfaced as a potential substitute for traditional hydraulic motors. Yet challenges such as torque pulsation and inefficient flow distribution persist in traditional designs. To improve performance and reliability, this paper proposed a digital radial piston hydraulic motor using several switching valves to distribute hydraulic oil, along with a comprehensive strategy to mitigate flow pulsation and enhance hydraulic transmission efficiency in digital hydraulic motors. The inherent torque pulsation characteristics are systematically investigated, revealing their dependence on valve actuation patterns and load dynamics. A novel torque pulsation mitigation design is introduced. Then, valve modeling and efficiency evaluation are developed; the phase-correction-based flow distribution method is conducted by optimizing valve sequencing; and simulations and experiments are carried out to demonstrate the feasibility. In conclusion, insights have been drawn to direct the design and control of radial piston digital hydraulic motors. This paper presents a potential solution for heavy-duty traction 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

The deposition of large-sized cuttings (or blocky cuttings) is a critical risk factor for stuck pipe incidents during the drilling of deep and extended-reach wells. This risk is particularly pronounced in well sections with long borehole trajectories and low drilling fluid return velocities, where it poses a substantial threat to wellbore cleanliness and the safe operation of the drill string. This study utilizes a self-developed visual experimental platform to simulate the deposition evolution of large-sized cuttings (20–40 mm in diameter) in the annulus under various wellbore inclinations and drilling fluid parameters. The stable height, lateral distribution characteristics, and response patterns of the resulting cuttings bed under different conditions were quantitatively characterized. Building upon this, a theoretical contact friction model between the drill string and the cuttings bed was employed to investigate how the bed height influences hook load during tripping and rotary torque during top drive operation. A mapping relationship was established between cuttings bed structural parameters and the resulting additional loads and torques. Results reveal significant interactive effects among drilling fluid velocity, fluid density, drill pipe rotation speed, and wellbore inclination on both cuttings bed development and associated drill string loads. Strong correlations were identified among these parameters. Based on these findings, a stuck pipe early-warning indicator system is proposed using frictional load thresholds, with clearly defined safety limits for cuttings bed height. Recommendations for optimizing cuttings transport parameters through coordinated control of fluid velocity, density, and rotary speed are also provided, offering theoretical support and engineering guidance for borehole cleaning strategies and stuck pipe risk prediction in large cuttings scenarios. Full article