Traction Torque Research Articles

ECHILIBRAREA MOTOARELOR ELECTRICE DE TRACȚIUNE PENTRU COMPENSAREA EFECTELOR TRANSFERULUI DE SARCINĂ

The individual drive of the axles of a vehicle produces a reduction of the axle adhesion, implicitly reducing the total traction force of the vehicle. The paper proposes eliminating load transfer effects by using an algorithm to redistribute the traction effort between the tractive axles equipped with electric traction motors. A case study is presented, using the balancing of the electric traction torque for an electric locomotive, using the load transfer effects compensation. The conclusions can be extended to maximise the traction of all types of vehicles, such as trailers, hybrid tractors, large harvesters, and Diesel-electric locomotives.

Analysis of mechanical characteristics and normal operating conditions of magnetic seals

Aiming at the leakage failure problem caused by the accidental disengagement of the sealing interface due to the failure of the magnetic seal force balance system, taking a certain type of aero-engine magnetic seal as an example, the mechanical analysis model of the magnetic seal is established, and the mechanical conditions for normal sealing work are deduced according to the set of equilibrium equations of force. The analysis process of the normal operation is proposed, and the calculation method of the key mechanical parameters of the magnetic seal is determined. On this basis, the influence of operating conditions on the normal operating mechanical conditions is analyzed. The results show that the primary sealing face contact pressure, the maximum contact pressure of the secondary sealing face, and the traction torque of the rotor determine the normal operating condition of the magnetic seal. Excessive chamber pressure and rotational speed will increase the contact pressure of the primary sealing face, leading to increased wear of the face and slippage between the O-Ring 1 and the shaft; too little differential pressure and rotational speed will lead to the disengagement of the graphite ring/stator, which ultimately leads to the failure of the seal. Severe vibration reduces the contact pressure of the primary sealing face and increases the risk of the primary sealing face disengagement.

Review of Energy-Saving Technologies for Electric Vehicles, from the Perspective of Driving Energy Management

The driving range of electric vehicles (EVs) is still an important factor restricting their development. Although the rising battery energy density has reached a bottleneck, which is a key constraint, the drive energy management strategy also has a significant effect and can improve the driving range of EVs, since wheel traction torque control can directly optimize the driving energy consumption of EVs. In order to comprehensively analyze the current research status of driving energy management and clarify its development direction, this review focuses on the driving energy management strategy of EVs and systematically summarizes the configurations and power distribution strategies of the dual-motor coupling drive system (DCDS), as well as torque vectoring control strategies of the decentralized drive system. Firstly, driving energy losses are analyzed in detail, which mainly include electric loss, tire slip energy dissipation, and the power of cornering resistance. Secondly, typical configurations of the DCDS are introduced, and the power distribution strategies of the DCDS are comprehensively reviewed. Finally, as an interesting energy-saving technology, energy-saving torque vectoring, generally applied to decentralized drive systems, is reviewed in detail in terms of its energy-saving pathways and control strategies, which are classified as front-and-rear torque vectoring and left-and-right torque vectoring. Research findings indicate that the driving range of EVs can be effectively increased by applying a driving energy management strategy based on several novel multi-power source drive systems. The development of a driving energy management strategy and the required novel drive systems will be a valuable and crucial direction for further energy conservation in EVs.

Modeling of the Wear Process of a Locomotive Wheelset and Rail During Sliding in a Curve

Purpose. This article is aimed at analyzing the wear process of locomotive wheelset and rail bands in curved sections of the rail track using the formalization of the ridge wear indicator for the wheelset slippage cycle. Methodology. In the process of developing a model for the wear of a locomotive wheelset, the phenomenon of slippage during the realization of traction torque was considered and the sliding speed functions at the point of contact between the wheel and the rail were determined. On the basis of the obtained functions, an analytical expression for determining the wear factor of the rims and ridges is proposed. To simplify practical calculations, the concept of the relative wear rate of the wheel ridge is introduced and an analytical expression for its determination is proposed. Findings. Our studies show that the slippage of locomotive wheelsets during the realization of traction torque is one of the decisive factors that determines the wear of the ridges. A significant reduction in the resulting ridge slip during slippage can be achieved by reducing the response time of anti-skid devices. It should also be noted that the resulting slip decreases to a greater extent than the speed of the snowplow protection increases. Originality. In this study, for the first time, a model of the wear process of wheel set tires and rims during locomotive slippage is proposed in a curve, where the wheel rim wear factor is represented as the total work of friction forces per slippage cycle. Practical value. The proposed analytical model can be used to predict the service life of locomotive wheel sets and to standardize train weights on railroad sections with a complex track plan and profile.

Dynamic characteristics analysis of gear transmission and its support bearings of high-speed train on the curve

The gear transmission in high-speed trains is crucial for transmitting the traction torque. Its dynamic characteristics impact the system's reliability and safety. Additionally, the gear transmission and its support bearings can be affected by wheel-rail interactions, particularly on curves with larger centrifugal forces. To address this, a spatial vehicle-track coupled dynamics model that considers the complete power transmission path and mechanical structure of the gear transmission is proposed. The model considers factors such as time-varying mesh stiffness, dynamic transmission error (DTE), time-varying support stiffness, and internal interactions of the gearcase bearing. Results indicate that when a high-speed train passes through a curve, the derailment coefficient and lateral force of the wheelset are less on the right curve due to the lateral component of the mesh force, but the opposite occurs on the left curve. The centrifugal effect affects the contributions of the lateral and vertical motions of the gear pair, which are balanced by the torsional motions of the components in the power transmission path. Additionally, the internal interactions between the rolling elements and races are intensified due to track irregularity and gear engagement, but the centrifugal effect of the pinion can be ignored.

Improved Super-Twisting Non-Singular Fast Terminal Sliding Mode Control of Interior Permanent Magnet Synchronous Motor Considering Time-Varying Disturbance of the System

To solve the problems that control performance of high torque traction interior permanent magnet synchronous motor (IPMSM) is degraded by parameter perturbation and unknown disturbance, this paper proposes a novel Improved Super-Twisting non-singular fast terminal sliding mode control strategy (IST-NFTSMC) for IPMSM based on Extended Nonsingular Fast Terminal Sliding Mode Disturbance Observer (ENFTSMDO). Firstly, the mathematical model of IPMSM under parameter perturbation is established; Then, an improved Super-Twisting nonsingular fast terminal sliding mode speed controller (IST-NFTSMC) based on extended nonsingular fast terminal sliding mode disturbance observer (ENFTSMDO) is designed, in which the improved Super-Twisting control law designed can effectively weaken the chattering of traditional NFTSMC, and ENFTSMDO can more accurately observe the unknown disturbance part of the system in real-time than ESMDO; Finally, compared with PI control and traditional NFTSMC control by simulations and experiments, the method proposed has merits of accelerating convergence, improving steady-state accuracy and minimizing the current and torque pulsation.

Fatigue life evaluation of automotive mechanical components by using smart design algorithm

AbstractThe aim of this work is to develop a so‐called “smart design” in MATLAB™ environment. The design process consists of an innovative and automatic algorithm aimed at rapidly evaluating the fatigue damage of automotive mechanical components, starting from the load cycle that the component is subjected. In this work, the target component is the front halfshaft of a sport utility vehicle. The algorithm works as follows. A driving cycle has been acquired through an experimental setup consisting of a control unit, a GPS and an OBD port. A mathematical model of the vehicle, based on longitudinal vehicle dynamics, has been developed in Simulink™ environment to evaluate the traction torque at the wheel. A torsional fatigue tests campaign has been carried out on nine front halfshafts of the vehicle to evaluate the torque amplitude–number of cycles curve of the component. The output histories, computed with the rainflow method, have been referred to a load ratio R = −1, according to the experimental fatigue tests, by the application of three different mean stress fatigue criteria: Goodman, Gerber, and Morrow. At the end, cumulative fatigue damage on the component has been evaluated by the application of the Palmgren–Miner rules. The results show that the Goodman criteria, with a fatigue damage value of around 20%, represents the most precautionary criteria for the fatigue design of an automotive component.

Non-uniform roller-race contact performance of bearings along width in the rotor-bearing system under dynamic loads

Under complex dynamic loads, the motions of the rotor and bending of the shaft can make the inner and outer races being of support bearings nonparallel in the rotor-bearing system, which will significantly affect the contact performance between the roller and race of support bearings. In this study, a rotor-bearing system with a cantilevered pinion is established by coupling the kinematic equations of the rotor with the determination of deflection deformation of the shaft. The time-varying mesh stiffness of gear pair, interactions between the roller and race of support bearings, and dynamic forces induced by dynamic rotor eccentricity are comprehensively considered in this model. In addition, a spatial rolling bearing dynamics model considering the radial load distribution along width and flexible roller is especially involved in this dynamic system using the slice method. The effect of traction torque, rotor eccentricity, and external excitation is analyzed. The results indicate that the non-uniform loads induced by gear engagement, dynamic rotor eccentricity, and external excitation will lead to local fatigue failures for support bearings. The fatigue lives of bearings are significantly lower than those calculated based on the static loads. Taking the traction motor of a railway locomotive as an example, this study is proven to be capable to provide a more reasonable method to investigate the service conditions of rolling bearings and assess the corresponding fatigue lives.

Real-Time Predictive Control of Path Following to Stabilize Autonomous Electric Vehicles Under Extreme Drive Conditions

A novel real-time predictive control strategy is proposed for path following (PF) and vehicle stability of autonomous electric vehicles under extreme drive conditions. The investigated vehicle configuration is a distributed drive electric vehicle, which allows to independently control the torques of each in-wheel motor (IWM) for superior stability, but bringing control complexities. The control-oriented model is established by the Magic Formula tire function and the single-track vehicle model. For PF and direct yaw moment control, the nonlinear model predictive control (NMPC) strategy is developed to minimize PF tracking error and stabilize vehicle, outputting front tires’ lateral force and external yaw moment. To mitigate the calculation burdens, the continuation/general minimal residual algorithm is proposed for real-time optimization in NMPC. The relaxation function method is adopted to handle the inequality constraints. To prevent vehicle instability and improve steering capacity, the lateral velocity differential of the vehicle is considered in phase plane analysis, and the novel stable bounds of lateral forces are developed and online applied in the proposed NMPC controller. Additionally, the Lyapunov-based constraint is proposed to guarantee the closed-loop stability for the PF issue, and sufficient conditions regarding recursive feasibility and closed-loop stability are provided analytically. The target lateral force is transformed as front steering angle command by the inversive tire model, and the external yaw moment and total traction torque are distributed as the torque commands of IWMs by optimization. The validations prove the effectiveness of the proposed strategy in improved steering capacity, desirable PF effects, vehicle stabilization, and real-time applicability.

Dual-objective torque control of electric vehicles drivetrain with robust global finite-time stability guarantee

The low-frequency torsional vibration caused by a sudden input torque change seriously affects electric vehicles' comfort and dynamic performance (EVs). This paper proposes a novel torque controller with robust global finite-time stability based on terminal sliding mode control to achieve the dual objectives of anti-jerk control and traction torque control. For this purpose, a general second-order system of EVs drivetrain with a disturbance term is established, and a new finite-time terminal sliding surface is designed. The proposed finite time torque controller (FT-TC) includes a finite-time sliding mode disturbance observer for real-time disturbance estimation and a finite-time sliding mode motor controller for calculating motor torque control law. In addition, the elimination of inherent chattering of the controller is considered in this paper. Finally, the proposed FT-TC is verified and compared with parallel double-loop PID controller and sliding mode controller on the Matlab/Simulink platform and an electric SUV platform under the condition of suddenly pressing/releasing the accelerator pedal during starting. The results indicate that the proposed FT-TC is effective and has a better synthetic evaluation performance in achieving the dual objectives.

ANALYSIS OF WAYS OF INCREASE OF TRACTION AND ENERGY PROPERTIES OF WHEELED ELECTRIC TRACTORS OF TRACTION CLASS 0,6

The article searches for and analyzes the design parameters of a wheeled electric tractor, which provide maximum efficiency and economy in the entire range of traction forces of the electric tractor in order to improve the traction and energy properties. Also, modern developments of new electric tractors in Ukraine were analyzed, bright examples are given, which are currently being developed and modernized. The choice of tractor layout is analyzed. Models of tractors with different axle speeds are analyzed, the possibilities of further calculation of electric tractors with the help of generalized mathematical models are considered, such as traction motor models, battery operation models, electric tractor control system models, traction torque determination and for comparison of ICE model and traction calculation

A study of wheel wear on a high-speed railway motor car

Wheel/rail wear is one of the key issues in the safe operation of a high-speed railway motor car. This paper analyzes and predicts the wheel wear evolution of motor car during the long-term operation process. Firstly, the detailed motor car with gear transmission systems and trailer car of the high-speed train, which take into account various non-linear factors such as dampers, bump stops, wheel/rail contact relation, etc., are developed to obtain interaction force between wheel and rail. Secondly, according to the tread update strategy based on fixed travel distance, a novel wheel wear prediction model integrating the Archard wear model and previous dynamics system is established. In order to more accurately obtain the dynamic responses of the motor car, the comprehensive gear transmission system coupling with motor bogie is also built, which considers the time-varying mesh stiffness and gear shift coefficient. And the corresponding traction characteristic curve is also applied to the gear transmission system. Finally, the wheel wear evolution in one re-profiling cycle is simulated to verify the developed model, and the wheel wear mechanism is investigated in detail. Furthermore, the influence of traction velocity on wheel wear is also investigated. The simulation shows that the cumulative wear amount of both two cars increases gradually and the wear rate decreases gradually with traveling mileage, but the wear rate of the trailer car decreases faster than that of the motor car due to larger longitudinal creepage and longitudinal creep force induced by traction torque. Moreover, the max wheel wear depth and wear bandwidth for motor car gradually increase with traction velocity. While the discrepancies of the max wheel wear depth and wear bandwidth for trailer car are small under different speeds.

Anti-jerking and traction torque compensation strategy for P3 + hybrid electric vehicle during power upshift

In this study, an anti-jerking and traction torque compensation strategy for P3 + hybrid electric vehicle (HEV) equipped with hybrid automated mechanical transmission (HAMT) during power upshift is proposed. Firstly, to investigate the power upshift characteristics, a powertrain model with three torque ports and flexible drive shaft is established. Secondly, based on the established powertrain model, a hierarchical structure optimization strategy for power upshift is developed. The optimization strategy makes full use of the fast and accurate torque response of the traction motor, aims at simultaneously suppressing the longitudinal jerk and compensating the traction torque, solves the optimal traction motor torque to improve the power upshift performance of P3 + HEV. Finally, a layer-by-layer simulation and a real vehicle test of the power upshift process from first gear to second gear are implemented to verify the effectiveness of the proposed optimization strategy. The verification results show that the proposed strategy can realize smooth and traction torque uninterrupted power upshift process at the same time. Compared with the traditional PI controller the proposed optimization strategy can achieve smaller longitudinal jerk.

Important powertrain dynamics for developing models for control of connected and automated electrified vehicles

Connected and Automated Vehicles (CAV) technology presents significant opportunities for energy saving in the transportation sector. CAV technology forecasts vehicle and powertrain power needs under various terrain, ambient, and traffic conditions. Integration of the CAV technology in Hybrid Electric Vehicles (HEVs) provides the opportunity for optimal vehicle operation. Indeed, Hybrid Electric Vehicle powertrains present high degrees of flexibility and possibility for choosing optimum powertrain modes based on the predicted traction power needs. In modeling complex CAV powertrain dynamics, the modeler needs to consider short-time scale powertrain dynamics, such as engine transients, and hysteresis of mode-switching for a multi-mode HEV. Therefore, the powertrain dynamics essential for developing powertrain controllers for a class of connected HEVs is presented. To this end, control-oriented powertrain dynamic models for a test vehicle consisting of full electric, hybrid, and conventional engine operating modes are developed. The resulting powertrain model can forecast vehicle traction torque and energy consumption for the specified prediction horizon of the test vehicle. The model considers different operating modes and associated energy penalty terms for mode switching. Thus, the vehicle controller can determine the optimum powertrain mode, torque, and speed for forecasted vehicle operation via utilizing connectivity data. The powertrain model is validated against the experimental data and shows prediction error of less than 5% for predicting vehicle energy consumption. The model is used to create energy penalty maps that can be used for CAV control, for example fuel penalty map for engine torque changes (10–40 Nm) at each engine speed. The results of model-based optimization show optimum switching delays ranging from 0.4 to 1.4 s to avoid hysteresis in mode switching.

Safe Reinforcement Learning for an Energy-Efficient Driver Assistance System

Reinforcement learning (RL)-based driver assistance systems seek to improve fuel consumption via continual improvement of powertrain control actions considering experiential data from the field. However, the need to explore diverse experiences in order to learn optimal policies often limits the application of RL techniques in safety-critical systems like vehicle control. In this paper, an exponential control barrier function (ECBF) is derived and utilized to filter unsafe actions proposed by an RL-based driver assistance system. The RL agent freely explores and optimizes the performance objectives while unsafe actions are projected to the closest actions in the safe domain. The reward is structured so that driver's acceleration requests are met in a manner that boosts fuel economy and doesn't compromise comfort. The optimal gear and traction torque control actions that maximize the cumulative reward are computed via the Maximum a Posteriori Policy Optimization (MPO) algorithm configured for a hybrid action space. The proposed safe-RL scheme is trained and evaluated in car following scenarios where it is shown that it effectively avoids collision both during training and evaluation while delivering on the expected fuel economy improvements for the driver assistance system.

Residual Policy Learning for Powertrain Control

Eco-driving strategies have been shown to provide significant reductions in fuel consumption. This paper outlines an active driver assistance approach that uses a residual policy learning (RPL) agent trained to provide residual actions to default power train controllers while balancing fuel consumption against other driver-accommodation objectives. Using previous experiences, our RPL agent learns improved traction torque and gear shifting residual policies to adapt the operation of the powertrain to variations and uncertainties in the environment. For comparison, we consider a traditional reinforcement learning (RL) agent trained from scratch. Both agents employ the off-policy Maximum A Posteriori Policy Optimization algorithm with an actor-critic architecture. By implementing on a simulated commercial vehicle in various car-following scenarios, we find that the RPL agent quickly learns significantly improved policies compared to a baseline source policy but in some measures not as good as those eventually possible with the RL agent trained from scratch.

Vehicle Tire Traction Torque Estimation Using a Dual Extended Kalman Filter

Abstract Vehicle tire traction torque, heavily dependent on vehicle speed and tire stiffness, is critical for improving vehicle traction performance. However, due to the limitation of existing technology and sensor cost, it becomes rather expensive to accurately measure the vehicle tire traction torque and/or other vehicle variables directly. This paper proposes to estimate the tire traction torque by estimating vehicle speed (vehicle state) and tire stiffness simultaneously based on a few available low-cost measurements from any production vehicle. Specifically, the tire and full vehicle dynamics are considered to form a unified traction torque estimation model under various vehicle operational conditions. Estimation of vehicle speed and tire stiffness is formulated into a dual-estimation problem of system states and parameters. A recursive real-time implementable solution for the dual-estimation problem is realized with the help of dual extended Kalman filter (DEKF) algorithm. The effectiveness of the proposed algorithm under different vehicle operating conditions is validated by comparing the estimated results with directly measured ones as well as those from existing estimation approaches. It is found that for a 4-wheel driving vehicle, under clutch overtaken condition, for the best case, the absolute mean square error (ASME) improves by around 20 Nm, and the relative mean square error (RMSE) reduces 12%; and under clutch slip condition, the absolute mean square error improves by around 40 Nm, and the RMSE reduces 6%.

ПОИСК РАЦИОНАЛЬНЫХ ТЕХНИЧЕСКИХ РЕШЕНИЙ ТЕПЛОВОЗА ДЛЯ ВОСТОЧНОГО ПОЛИГОНА

The purpose of the study is to search for rational engineering solutions for the main autonomous locomotive for the Eastern range of OAO Russian Railways.
 Research methods: methods of physical and field experiments, analytical methods for calculating the dynamics of the rolling stock. 
 Research results and novelty: it is established that the use of a four-axle truck of a diesel locomotive TEM7 does not allow to create a locomotive that meets all the requirements of OAO Russian Railways, and the design of truck TEM7 is irrational for mainline locomotives; it is proved that the one-sided arrangement of brake blocks leads to deterioration in the locomotive braking properties. The bearing and axial towline, despite the use of an asynchronous engine, has an unsprung mass 1.5 times greater than that of the previously produced domestic analogue with a collector engine and almost the same mass of the wheel-motor unit; dynamic moments in the drive due to the lack of elastic elements during prolonged operation can reach 56% of the traction torque, which worsens the traction properties of the locomotive. 
 Conclusion: it is advisable to carry out a design study of the drive variant with a support-frame asynchronous traction engine and an axial gearbox, as well as to conduct a technical and economic analysis and design study of a cheaper version of a diesel locomotive with sections on three two-axle bogies, maximally unified with electric locomotives, with a booster tanker module and AC-DC transmission with axial regulation of eight-pole collector motors with support-frame suspension.

Slip-Clutch Torque Estimation via Real-Time Adaptive Lookup Table

Abstract Transfer case clutch is crucial in determining traction torque distribution between front and rear tires for four-wheel-drive (4WD) vehicles. Estimating time-varying clutch surface friction coefficient is critical for traction torque control since it is proportional to the clutch output torque. As a result, this paper proposes a real-time adaptive lookup table strategy to provide the time-varying clutch surface friction coefficient. Specifically, the clutch-parameter-dependent (such as clutch output torque and clutch touchpoint distance) friction coefficient is first estimated with available low-cost vehicle sensors (such as wheel speed and vehicle acceleration); and then a clutch-parameter-independent approach is developed for clutch friction coefficient through a one-dimensional lookup table. The table nodes are adaptively updated based on a fast recursive least-squares (RLS) algorithm. Furthermore, the effectiveness of adaptive lookup table is demonstrated by comparing the estimated clutch torque from adaptive lookup table with that estimated from vehicle dynamics, which achieves 14.8 Nm absolute mean squared error (AMSE) and 2.66% relative mean squared error (RMSE).

Study on Mechanism Analysis of Skidding Prediction for Electric Vehicle Based on Time-Delay Effect of Force Transmission

The electric vehicle anti-skidding control system is used to ensure the stability of the vehicle under any circumstances. There is a typical feature in most anti-skidding detection methods; the skidding occurs first, and then the detection is performed. For methods that rely on slip rate detection, more accurate vehicle speeds are required, which are often difficult to accurately observe. The previous method was detection and could not do prediction. Skidding prediction can improve driver reaction time and increase safety. Therefore, this paper proposes a prediction method that does not depend on the slip rate. The skidding prediction can be performed by relying on the driving torque, as well as the wheel speed. In this paper, the characteristics of the transmission from the driving force to the friction force in the vehicle model are analyzed. As for the distributed electric vehicle, the slip factor was designed with traction torque and friction force for skidding prediction by its sharp increase before the maximum adhesion point. The variation in the slip factor and time period of skidding are revealed. A multi-information merged prediction model is designed to improve reliability. The co-simulation and experimental verification based on the physical skidding simulation platform are carried out.