Search Results (391)

Tractor rollover is a persistent worldwide problem that does not yet have a fundamental solution. Adjusting the tractor’s attitude or configuration may enhance mobility under complex terrain conditions to prevent rollover. Therefore, in this study, an attitude adjustment method for offsetting the height difference between the uphill and downhill sides is proposed to adjust a tractor’s posture. Kinematic models are established for front-wheel, four-wheel, and articulated body steering modes. Steering mathematical models are developed for the three modes to describe the effects of posture change on tractor steering instability. This method predicts the steering stability by analyzing tire contact forces. Both the critical slope angle and steering speed are derived and used to predict instability while taking the steering radius into consideration. Considering a tractor’s attitude, simulations are conducted under two conditions; namely, attitude adjustment and level attitude. The results show that attitude adjustment is an effective method to enhance a tractor’s steering stability to avoid overturning. Furthermore, the models presented here provide theoretical references and optimization directions to prevent lateral overturning during tractor steering. Full article

As driving becomes more automated, the driver–car interaction is changing. The steering wheel, traditionally the main interface between the driver and the vehicle, is reduced to being a part of the environment in autonomous driving. Its influence on kinematic reactions to decelerations without a prompt to take over control of the vehicle is still unknown. Therefore, low-speed sled tests with seven female volunteers matching 5th or 50th percentile anthropometrics were performed, including three upright trials and two reclined trials at backrest angles of 23° and 45° during a standardized braking pulse. A steering wheel was placed in front of the volunteers to limit available space when moving forward. Kinematic analysis focused on the forward head movement. The study showed that no targeted hand grasping towards the steering wheel occurred in either backrest configuration. Head forward excursion was slightly higher in the first upright trial for some volunteers. Less variation and lower absolute forward excursion of the head were found in the reclined trials. Without the need for a required vehicle takeover, no grasping of the steering wheel was observed among the participants studied. Full article

Distributed-drive electric vehicles (DDEVs) improve braking stability through independent four-wheel braking torque control, yet their complex multi-brake systems are prone to braking faults that cause loss of longitudinal and yaw stability. This study investigates DDEV braking performance under normal and faulty conditions and proposes a three-module braking stability control strategy consisting of demand torque calculation, fault constraint reconstruction, and fault-tolerant control. The fault constraint reconstruction module establishes braking capacity boundaries based on real-time fault and vehicle state data and constrains four-wheel braking torque via target projection. A composite fault-tolerant control scheme combining active front steering (AFS) and braking torque distribution is developed to suppress stability degradation. The AFS adopts a sliding-mode algorithm for accurate front wheel steering regulation, while a quadratic programming algorithm optimizes four-wheel braking torque allocation. Hardware-in-the-loop simulations are conducted for straight line and double lane change braking under single wheel regenerative, mechanical, and complete braking failure conditions. The results reveal that the proposed strategy limits peak yaw rates to 1.1 deg/s, 2.8 deg/s, and 3.5 deg/s in faulty regenerative, mechanical, and complete straight line braking, respectively, and achieves excellent yaw rate and trajectory tracking during faulty double lane change braking. This work provides an effective solution for DDEV braking stability optimization and fault-tolerant control. Full article

Lane-Keeping Assist Systems (LKAS) are widely used in modern passenger vehicles to support lateral vehicle control and reduce the risk of unintended lane departure. Although LKAS performance is commonly evaluated in relation to perception, control, and sensor fusion, the observable vehicle response may also depend on the mechanical condition of the chassis. This study presents a qualitative, measurement-based evaluation of the influence of intentionally introduced front-wheel toe misalignment on the observable response of a production LKAS under controlled proving-ground conditions. Experimental tests were conducted on the highway module of the ZalaZONE proving ground using a Lexus RX 450h equipped with a factory-installed LKAS function. Three front-wheel toe configurations were investigated: factory-specified alignment, single-wheel toe misalignment, and severe toe misalignment affecting both front wheels. Measurements were performed at 70, 90, and 110 km/h on straight and curved road sections. Vehicle speed, steering angle, lateral acceleration, and GNSS-based position data were recorded using CAN- and GNSS/IMU-based data acquisition. The qualitative comparison of the measured signal profiles indicated that the misaligned configurations were associated with a shifted steering-angle operating range and less uniform steering and lateral-acceleration responses. The most pronounced visible differences occurred under the severe toe-misalignment condition, particularly at higher speeds and in the curved section. As the analysis did not include quantitative effect measures or statistical comparisons, these observations are interpreted as exploratory tendencies rather than statistically validated changes in LKAS performance. The findings suggest that front-wheel toe condition should be considered in the measurement-based assessment, maintenance, and calibration of ADAS-equipped vehicles. Full article

This paper presents the development of a multi-domain simulation for the Porsche Taycan’s all-wheel-drive (AWD) electric propulsion system to investigate the impact of the rear drive unit’s two-speed transmission on performance and drive quality during maximum acceleration. This study was undertaken independent of the vehicle and propulsion system OEM. A lumped-parameter model of the front and rear electric drive units (EDU) and the high-voltage battery was developed and calibrated against the published data for key benchmarks, including 0–100 kph acceleration times and peak longitudinal acceleration. The mechanical shifting mechanism was reverse-engineered to simulate high-performance shift trajectories. To manage the transition, a clutch control scheme integrates a reduced-order clutch-to-clutch model featuring a feedforward (FF) torque estimator and a closed-loop feedback (FB) controller to achieve target input shaft speeds and shift durations. The study concludes with a comprehensive analysis of the propulsion system’s behavior at a battery state of charge of 96% and 25% and three electric motor speeds at which the upshift is commanded. The simulation results demonstrate that executing an early upshift at 10,700 rpm with 96% of SOC yields a 0.100-s inertia phase shift time, restricts the clutch thermal dissipation to 21 kJ, and achieves an 8-s velocity of 203.4 kph, outperforming the upshift at 15,300 rpm (0.210 s, 34 kJ, and 202.8 kph). Furthermore, the transient regenerative braking on the rear axle during the inertia phase reduces the peak current draw from 675 A to 87 A, recovering the DC bus voltage to enable cross-axle torque boosting on the front axle. Full article

This paper presents the research, development, and functional validation of an original rear suspension system designed for hybrid reverse trike vehicles (two guided wheels on the front axle and a twin-tire-driven assembly at the rear). Conventional configurations featuring a single rear wheel exhibit severe limitations regarding lateral stability under critical dynamic regimes and induce roll-induced torsional loading in flexible chain drives. The proposed solution utilizes a twin-tire rear assembly integrated into an articulated suspension mechanism with two degrees of freedom (2 DoF), which reconfigures the geometric stability polygon from a triangle into an isosceles trapezoid. A mathematical model based on tire dynamics and tire slip phenomena demonstrates that introducing a controlled roll stiffness on the rear axle stabilizes the slip angles, ensuring a neutral and predictable steering behavior. Structural validation via finite element analysis (FEA) performed in SOLIDWORKS Simulation on the entire assembly under a conservative combined load scenario (2400 N vertical force shared by the two wheel bearings, 2400 N lateral force, and 1200 N tractive force) indicated a minimum factor of safety of 1.26 on S275N structural steel, confirmed by an eleven-run mesh independence study. Finally, the system’s functionality was experimentally confirmed through the manufacturing and road testing of a full-scale (1:1) demonstrator vehicle powered by an 1129 cc Boxer engine, highlighting a measurable increase in rollover resistance and trouble-free operation of the two-stage chain drive throughout the test program. A numerical evaluation shows that for rear-biased vehicles of the category the proposed axle raises the rollover-related lateral acceleration threshold by up to 54% and replaces the strongly oversteering balance of the single-wheel layout with a near-neutral, tunable one. Full article

Speed controllers for electric micromobility (EMM) drives are increasingly developed with Model-Based Design and deployed as automatically generated code, yet the cost that a given control law actually imposes on the target, and the mechanism by which competing laws differ once deployed, are seldom reported. This paper addresses both questions on an EMM-class test bench built around a 36 V, 250 W in-wheel BLDC motor. A proportional-integral (PI) regulator and a first-order Takagi-Sugeno (TS) fuzzy regulator are specified in Simulink, auto-coded to ANSI-C by Embedded Coder, and deployed unchanged on an STM32F446RE target driving a custom three-phase inverter through six-step Hall commutation. Over a six-step, 180 s duty cycle reaching 21.1 km/h, the two regulators are shown to occupy opposite ends of the speed-versus-damping trade-off. On the 30 to 100 RPM ascending step under load, the PI reaches the set-point in $0.4\pm 0.1$ s with $21.6\%$ overshoot and the TS in $2.7\pm 0.1$ s with $1.5\%$ overshoot, both quoted at the resolution of the 10 Hz acquisition, and over the complete duty cycle, a window that also contains segments on which neither regulator has control authority, the TS lowers the tracking RMSE by 9.4%. A structural analysis of the deployed firmware excludes the realisation form as the cause. The positional and incremental forms are algebraically equivalent while the command is unsaturated, which is the regime of the step above. Under saturation, the incremental accumulator of the TS is not clamped and winds up exactly as the positional PI integrator does. The two loops are also shown to share the same unfiltered speed feedback and the same command saturation limits. The difference is traced instead to the effective gains realised by the seven consequents. Far from the set-point, the TS applies an integral gain three to twelve times weaker than the PI for a comparable proportional gain. A fixed-gain PI in that range is predicted to reproduce the response for one eighth of the Flash. The embedded cost of both regulators is then quantified on the target from the linker map, the fuzzy controller occupying 2325 Bytes of Flash against 266 Bytes for the PI, a factor of 8.7, and 200 Bytes of stack against 32 Bytes, a factor of 6.3, rising to 248 Bytes against 32 Bytes when the complete call tree is counted, for 0.45% of the available Flash. The complete platform, comprising the inverter, the Hall front end, the auto-generated firmware, and a Python supervisory interface, is described together with its deployed timing, PWM, and saturation parameters. Full article

Background/Objectives: Healthcare professionals have begun utilizing a wheelie task for balance assessment in para sport athletes. With recent advancements to incorporate dual-task exercises, the purpose of this study was to evaluate baseline wheelie performance during single and dual-task and measure 1-week and 45-day reliability in a sample of collegiate para sport athletes. Methods: Twenty-five (male n = 14, 56.0%) collegiate para sport athletes completed a wheelie assessment under single and dual-task conditions. Measures consisted of standardized biomechanical errors (e.g., front wheels touching ground, changing grip on wheel) as scored by a single clinician during eyes-open and eyes-closed positions. Assessments were repeated 7 ± 2 days and 45 ± 7 days later. Results: At baseline, there were no differences with dual-task exercise during eyes-open wheelie balancing (p = 0.096). No differences were observed from single to dual-task in the eyes-closed position (p = 0.154) at baseline, but there were significantly more errors during this position at both the 1-week (p = 0.005) and 45-day (p = 0.004) retest intervals. Fair to moderate correlations existed for both eyes-open and eyes-closed positions during single and dual task across 1-week (rs ≥ 0.49) and 45-day (rs ≥ 0.40) retest intervals. Conclusions: The incorporation of dual-task exercises during the eyes-closed wheelie position appears to increase the difficulty of balance compared to single-task, possibly making it a useful assessment to evaluate balance in para-athletes. There is fair to moderate correlation of the wheelie during single and dual tasks over time. Future research is needed on dual-task compensation post-injury. Full article

To address inaccurate longitudinal speed acquisition, difficult road adhesion identification, and insufficient reliability of state inputs for traction control in dual-motor electric vehicles under low-adhesion, adhesion-transition, and drive-slip conditions, this paper proposes a state estimation method oriented to traction control. Four-wheel speeds, inertial measurement unit (IMU) signals, and vehicle dynamics are fused to establish a layered longitudinal speed estimation structure, including slip-confidence evaluation, inertial correction, kinematic and dynamic fusion, and multi-mode weight decision. Standard road adhesion curves, fuzzy inference, and recursive correction are further combined to estimate the peak adhesion coefficient and the optimal slip ratio online. CarSim/Simulink co-simulation results show that the root mean square errors of the proposed speed estimation method are 0.1226, 0.1728, 0.1070, and 0.0322 m/s under comprehensive driving, acceleration slip, emergency braking, and high-speed steering conditions, respectively. Under an adhesion-transition condition, the peak adhesion coefficient and optimal slip ratio can be updated rapidly with road changes. Application results suggest that the estimated states can provide useful inputs for front–rear axle traction coordination under the investigated low-adhesion conditions. Full article

To improve braking energy recovery in pure electric vehicles while maintaining a reasonable braking-force distribution, this study proposes a regenerative braking strategy based on a grey wolf optimizer (GWO)-optimized fuzzy control. A single-motor front-wheel-drive pure electric vehicle is modelled in terms of vehicle longitudinal dynamics, motor characteristics, and battery state of charge (SOC). A front–rear braking-force distribution strategy is developed based on the ideal braking-force distribution I-curve and ECE regulation constraints. A Mamdani fuzzy controller is then designed with braking intensity z and battery SOC as inputs and the front-axle regenerative braking-force distribution coefficient k as the output, enabling coordinated allocation between front-axle regenerative braking and mechanical braking. To reduce the dependence of fuzzy rules on expert experience, the GWO is used to optimize 25 fuzzy rules, and the proposed strategy is verified in MATLAB R2023b under a typical urban driving cycle. The results show that all strategies satisfy the braking demand. Compared with the unoptimized fuzzy control strategy, the optimized strategy reduces SOC consumption by 5.15% and increases recovered braking energy by 59.56%, indicating improved regenerative braking performance. Full article

The need to measure the geometric dimensions of a railway wheel during train motion at a speed of 120–150 km/h with an error below ±0.25 mm and to identify defects on the tread surface and flange is justified. A new optical measurement system that provides this measurement accuracy was developed. The wheel geometric parameters were measured, and defects were identified using square-wave pulsed laser radiation with a plane-parallel wavefront in the form of a 4 mm wide and 280 mm long line, with a pulse duration of 14 μs, formed using a newly designed collimator. A method was developed for selecting the laser pulse duration so that image blur would have an insignificant influence on the measurement results. Under these conditions, the wheel surface could be considered locally flat with respect to the incident laser radiation. The receiving modules were positioned relative to the rail surface so that the CMOS field of view covered a wheel-surface sector of 10°12′ from both sides and recorded the reflected radiation as a point cloud. To reduce stray illumination and reflections, a filter with a 12.6 nm bandwidth centered at 638.2 nm with a transmittance of 0.71 was installed in front of the CMOS matrix. A point-cloud processing algorithm was developed. Of 236 recorded profiles, 232 were processed successfully, corresponding to a successful-processing rate of 98.3%. Defects were detected in seven processed profiles and confirmed by control measurements. The geometric parameters were determined with a calculated error not exceeding 0.25 mm at 150 km/h. Complete wheel monitoring required 36 sequentially installed optical measurement modules developed in this work, approximately 1.4 times fewer than in comparable systems, for which the measurement error at 150 km/h was approximately ±0.6 mm and the reported defect identification reliability was 95%. Full article

In this paper, the concept of symmetry is applied to design active trajectory tracking control of autonomous distributed drive electric vehicles considering energy efficiency—that is, the construction and solution of active trajectory tracking controllers are symmetrical. This paper proposes a hierarchical control strategy consisting of upper-level control and lower-level control to improve trajectory tracking accuracy of DDEVs considering energy-efficiency characteristics. In the upper-layer control, a sliding mode active disturbance rejection (ADRC) controller is developed to control the front wheel steering angle and active yaw moment to achieve tracking of the desired trajectory, in which an extended state observer (ESO) is synthesized to estimate and compensate for internal model uncertainties and external environmental disturbances. In the lower-layer control, a multi-objective optimization algorithm based on Karush–Kuhn–Tucker (KKT) conditions is designed to realize the torque distribution control for improving energy efficiency and vehicle stability of the distributed drive electric vehicle. Finally, a joint simulation platform based on Matlab/Simulink-CarSim (version 2019) is established for simulation verification. The performances of ADRC, linear quadratic regulator controller (LQR), and model predictive controller (MPC) are compared in snake-like and double-lane-change maneuvers. Simulation results show that the proposed controller can effectively reduce motor energy consumption while maintaining trajectory tracking accuracy and handling stability. This work provides a certain engineering design solution for motion control of intelligent electric vehicles. Full article

This study proposes an integrated self-aligning-torque energy recovery and DC-bus voltage stabilization strategy for a permanent-magnet synchronous motor (PMSM)-driven steer-by-wire system in new energy vehicles. During the front-wheel return-to-center process, self-aligning torque may provide excess mechanical energy to the steering actuator. Instead of dissipating this energy through a braking resistor, the proposed strategy converts part of the self-aligning-torque-induced mechanical energy into electrical energy and feeds it back to the low-voltage DC bus. To avoid ambiguity in the operating-mode description, this paper distinguishes the standard PMSM torque–speed quadrants from the mechanical stages of the steering process. Regenerative operation is defined according to the condition ($T_e{\omega }_m<0$), corresponding to the second or fourth quadrant of the PMSM torque–speed plane, whereas the return-to-center regenerative stage refers to the self-aligning-torque-dominated stage of the steer-by-wire motion. Based on this definition, an electromechanical energy-flow model is established to describe the transfer path from self-aligning torque to the PMSM and then to the DC bus. Considering that regenerative energy injection may cause DC-bus voltage fluctuation or braking-resistor activation, a single-loop bus-voltage stabilization method based on active disturbance rejection control is developed. A third-order linear extended state observer is adopted to estimate the lumped disturbance caused by self-aligning-torque variation, current coupling, load variation, parameter uncertainty, and inverter loss. The observer bandwidth, controller gains, current limitation, and overvoltage protection mechanisms are further discussed to improve the practical implementability of the proposed control strategy. In addition, an energy-accounting method is introduced to distinguish total steering energy consumption, available self-aligning-torque mechanical energy, gross recovered electrical energy, system losses, net recovered energy, and recovery efficiency. Simulation and experimental results show that the proposed strategy can suppress DC-bus voltage rise, reduce braking-resistor energy dissipation, and achieve measurable steering-actuator-level energy recovery during repeated return-to-center maneuvers. The results verify the feasibility of using self-aligning-torque-induced regenerative energy in PMSM-driven steer-by-wire systems, while the actual vehicle-level energy benefit depends on the driving cycle, low-voltage load demand, battery charging acceptance, and converter efficiency. Full article

In-wheel motor (IWM) systems enable compact architectures and advanced control strategies, making them increasingly relevant in hybrid and electric vehicle applications. This work presents the design and the integration of a front-axle IWM system for a Formula SAE combustion vehicle, within a parallel hybrid configuration. The study includes vehicle dynamics analysis, battery pack sizing under strict regulatory constraints, and an initial evaluation of motor and transmission requirements. A MATLAB R2023a-based algorithm was developed to design and optimize a compact two-stage planetary gearbox. This structured and scalable approach supports future development phases and offers a valuable methodology for early-stage hybrid powertrain design. Full article

This study proposes a reduced-complexity nonlinear model predictive control (NMPC) framework for high-performance path tracking of a four-wheel-drive (4WD) autonomous vehicle. A 4WD sports car equipped with four independent wheel motors is used as the test vehicle. Although the vehicle has four motors, the proposed NMPC directly optimizes the front-wheel steering command and the rear-left and rear-right wheel torque commands, while the front-wheel torques are generated using a gain-based virtual 4WD distribution law. Trajectory optimization (TRO) is performed offline to generate the reference racing line and velocity profile, while the online NMPC controller tracks the optimized reference trajectory using the front-wheel steering command and the rear-left and rear-right wheel torque commands as control inputs. This structure reduces the control complexity while maintaining the ability to improve traction utilization and yaw response. Under the investigated simulation conditions on the Shanghai International Circuit, the proposed reduced-dimensional NMPC with rear-dominant virtual 4WD torque distribution reduces the simulated lap time while maintaining bounded path-tracking errors and satisfying the track-boundary constraints. As the torque distribution gain $K_r$ increases from 0 to 0.5, the lap time is reduced by approximately 10.3% (from 182.08 s to 163.30 s), while the maximum lateral tracking error remains below 0.33 m and the maximum heading-angle error remains below 2.95 deg for all stable cases. However, further increasing $K_r$ beyond 0.5 leads to degraded tracking performance or loss of stable path following because excessive front-wheel longitudinal force reduces the available lateral tire force for steering. These results indicate that an appropriate torque distribution gain can improve corner-exit acceleration and overall lap-time performance, whereas excessive front torque assistance may degrade tracking accuracy and vehicle stability. Full article