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An EPS system is used to improve the stability and safety of the car when steering while also simplifying the steering process. This article introduces a novel control solution for the EPS system called BSSMCPID. This algorithm combines two nonlinear techniques, BS and SMC, with the input signal corrected by a PID technique. This algorithm provides three new contributions compared to existing algorithms: reducing system errors and eliminating phase differences, ensuring stability even when exposed to external disturbances, and reducing power consumption. The system's stability is evaluated according to the Lyapunov criterion, while the algorithm's performance is evaluated based on numerical simulation results. According to the article findings, the RMS error of the steering column angle and steering motor angle values (controlled objects) is approximately zero, and the RMS error of the steering column speed and steering motor speed is about 0.01 rad/s, which is much lower than the results obtained with traditional BS and PID controllers. When the EPS system is controlled by the integrated nonlinear method proposed in this work, the output values always closely follow the reference values with negligible errors under all investigated conditions. Additionally, power steering performance increases as speed decreases or driver torque increases, which follows the ideal assisted power steering curve. In general, the responsiveness and stability of the system are always ensured when applying this algorithm. [ABSTRACT FROM AUTHOR]

This research introduces an innovative approach for End-to-End steering angle prediction and its control in electric power steering (EPS) systems. The methodology integrates transfer learning-based computer vision techniques for prediction and control with fuzzy signatures-enhanced fuzzy systems. Fuzzy signatures are unique multidimensional data structures that represent data symbolically. This enhancement enables the fuzzy systems to effectively manage the inherent imprecision and uncertainty in various driving scenarios. The ultimate goal of this work is to assess the efficiency and performance of this combined approach by highlighting the pivotal role of steering angle prediction and control in the field of autonomous driving systems. Specifically, within EPS systems, the control of the motor directly influences the vehicle's path and maneuverability. A significant breakthrough of this study is the successful application of transfer learning-based computer vision techniques to extract respective visual data without the need for large datasets. This represents an advancement in reducing the extensive data collection and computational load typically required. The findings of this research reveal the potential of this approach within EPS systems, with an MSE score of 0.0386 against 0.0476, by outperforming the existing NVIDIA model. This result provides a 22.63% better Mean Squared Error (MSE) score than NVIDIA's model. The proposed model also showed better performance compared with all other three references found in the literature. Furthermore, we identify potential areas for refinement, such as decreasing model loss and simplifying the complex decision model of fuzzy systems, which can represent the symmetry and asymmetry of human decision-making systems. This study, therefore, contributes significantly to the ongoing evolution of autonomous driving systems. [ABSTRACT FROM AUTHOR]

Recently, interest in functional safety has surged because vehicle technology increasingly relies on electronics and automation. Failure of certain system components can endanger driver safety and is costly to address. The detection of abnormal data is crucial for enhancing the reliability, safety, and efficiency. This study introduces a novel anomaly-detection method of designable generative adversarial network anomaly detection (DGANomaly). DGANomaly combines the data augmentation method of a designable generative adversarial network (DGAN) with a generative adversarial network anomaly-detection data classification technique. DGANomaly not only generates virtual data that are challenging to obtain or simulate but also produces a range of statistical design variables for normal and abnormal data. This approach enables the specific identification of normal and abnormal design variables. To demonstrate its effectiveness, the DGANomaly method was applied to an electric power steering (EPS) model when multiple degradations of gear stiffness, gear friction, and rack displacement were considered. An EPS model was constructed and validated using simulation programs such as Prescan, Amesim, and Simulink. Consequently, DGANomaly exhibited a higher classification accuracy than the other methods, allowing for more accurate detection of abnormal data. Additionally, a clearer range of statistical designs can be obtained for normal data. These results indicate that the statistical design variables that are less likely to fail can be obtained using minimal data. [ABSTRACT FROM AUTHOR]

Excessive cogging torque can cause torque fluctuations, noise, and vibration in electric power steering (EPS) motors, which is a key factor in the high-precision and high-performance optimization design of EPS motors for electric vehicles. This article takes a 12-slot 10-pole electric power steering motor for a certain car as an example. By establishing the corresponding electromagnetic field model and theoretical analysis of the motor, the influence of the pole arc coefficient and eccentricity parameters of the permanent magnet on the cogging torque of the electric power steering motor is explored. A comprehensive optimization scheme for reducing the cogging torque of the motor structure is proposed. The effectiveness of the designed scheme was verified through finite-element simulation and experimental testing of motor electromagnetism. Compared with the original design, the optimized structure of the EPS motor resulted in an 86.62% reduction in cogging torque during experimental testing. [ABSTRACT FROM AUTHOR]

The development of the automotive industry is associated with the rapid advancement of onboard systems. In addition, intensive development in the electronics and control systems industry has resulted in a change in the approach to the issue of assistance systems in vehicles. Classic hydraulic systems have been almost completely replaced by modern electric power steering (EPS) systems, especially in citizen vehicles. This paper focuses on fault detection algorithms for EPS, along with the available tools to aid development and verification. The article discusses in detail the current state of knowledge in this area. The principle of operation of the EPS system and the influence of the structure of the mechanical system on its operation, in particular the characteristics of the ground–tire contact, are presented. Various error identification methods are presented, including those based mainly on a combination of tests of real objects as well as those combined with modern hardware-in-the-loop (HIL) equipment and virtual vehicle environment software, enabling the development of new diagnostic methods, enhancing the security, reliability, and energy control in the vehicle. A review of the literature indicates that although many algorithms which enable fault detection at an early stage are described, their potential for use in a vehicle is highly limited. The reason lies in simplifications, including models and the operating EPS temperature range. The most frequently used simplification of the model is its linearization, which significantly reduces the calculation time; however, this significantly reduces the accuracy of the model, especially in cases with a large range of system operation. The need for methods to detect incipient faults is important for the safety and reliability of the entire car, not only during regular use but also especially during life-saving evasive maneuvers. [ABSTRACT FROM AUTHOR]

Aiming at the lack of adaptability of vehicle parameters under extreme conditions, this paper proposes an integrated control method for path tracking and lateral stability of distributed drive electric vehicles based on tire cornering stiffness adaptive model predictive control (MPC) scheme. The control method integrates active front steering and direct yaw control to improve the path tracking and lateral stability performance of distributed drive electric vehicles. Firstly, considering the influence of vertical load transfer, the tire cornering stiffness is estimated based on the extended Kalman filter (EKF) algorithm. Then, using this online updated tire cornering stiffness value, an adaptive MPC controller for path tracking and lateral motion stability of distributed drive electric vehicles is constructed. Meanwhile, a fuzzy sliding mode control (Fuzzy-SMC)–based longitudinal velocity controller is established to ensure the accuracy of velocity tracking. Also, according to the distributed driving characteristics of the controlled system, a tire torque distributor based on weighted pseudo-inverse (WPI) is designed with the minimum tire load rate as the optimization objective, where the road adhesion condition and the maximum output torque of the motor are considered as constraints. The simulation results show that the proposed integrated control method based on tire cornering stiffness adaptive model predictive control is robust and effective. Compared with constant cornering stiffness model predictive control–based control method, it can improve the vehicle path tracking accuracy and lateral motion stability under extreme conditions. [ABSTRACT FROM AUTHOR]

A hub motor is integrated into an electric wheel. The external excitation is complex and the heat dissipation conditions are poor. The working temperature of the hub motor easily becomes too high, resulting in large fluctuations in the output torque, which affect its service life. Taking a four-wheel hub-driven electric vehicle as the research object and aiming to resolve the issue of inaccurate prediction of the output torque of the hub motor in the real operating environment of the vehicle, a method for analyzing the temperature rise and torque characteristics of the hub motor considering multisource excitation and magnetic–thermal bidirectional coupling is proposed. First, the multisource excitation transmission path of the hub motor and the coupling principle of the road-electric wheel-vehicle body suspension system are analyzed from three aspects: the electromagnetic effect of the hub motor itself, the tire-ground effect, and the interaction between suspension (body) and electric wheel. We concluded that the load torque and air gap change in the motor are the key factors of its torque characteristics. On this basis, a dynamic model of the road-electric wheel-suspension-vehicle body system, an electromagnetic field model of the hub motor, and a temperature field model are established, and the influence of load torque and air gap change on the loss of in-wheel motor under multisource excitation is analyzed. Furthermore, based on the magnetic–thermal bidirectional coupling method, the motor loss under the combined action of load torque and air gap change is introduced into the temperature field model, and combined with the electromagnetic field model of the hub motor, the temperature distribution law and torque characteristics of the hub motor are accurately predicted. Finally, the accuracy and effectiveness of the calculation results of the temperature and torque characteristics of the hub motor are verified via an electric wheel bench test. [ABSTRACT FROM AUTHOR]

This document is a summary of a special issue on vehicle dynamics and road safety. The articles included in the issue cover a wide range of topics related to engineering-based technologies and measures for improving road safety and ride comfort. The articles discuss various aspects such as the impact of pavement aggregate grain size on skid resistance, technical solutions for bridge refurbishment, the effect of steering inputs on vehicle response to crosswinds, and the characterization of forces in the transportation of bulk and liquid commodities. The special issue provides readers with insights into the progress and achievements of different countries in the field of vehicle dynamics and road safety, and highlights advanced solutions for autonomous driving research, climate change aspects in transport, vehicle functional safety, and driver assistance systems. [Extracted from the article]

This paper presents the design and the non-linearity optimization of a new vertical non-contact angle sensor based on the electromagnetic induction principle. The proposed sensor consists of a stator part (with one solenoidal excitation coil and three sinusoidal receiver coils) and a rotor part (with six rectangular metal sheets). The receiver coil was designed based on the differential principle, which eliminates the effect of the excitation coil on the induced voltage of the receiver coil, and essentially decouples the excitation field from the eddy current field. Moreover, the induced voltages in the three receiver coils are three-phase sinusoidal signals with a phase difference of 10°, which are linearized by CLARK transformation. To minimize the sensor non-linearity, the Plackett–Burman technique was used, which identified the stator radius and the rotor blade thickness as the key factors affecting the sensor linearity. Then, the particle swarm algorithm with decreasing inertia weights was utilized to optimize the sensor linearity. A sensor prototype was made and tested in the laboratory, where the experimental results showed that the sensor non-linearity was only 0.648% and 0.645% in the clockwise and counterclockwise directions, respectively. Notably, the non-linearity of the sensor was less than −0.696% at different speeds. [ABSTRACT FROM AUTHOR]

In this paper, a novel electric-hydraulic power steering (EHPS) system and a vehicle stability coordination control algorithm are proposed which can not only ensure the accuracy of the trajectory tracking but also solve the coordination control problem between the stability of the lateral control and the stability of the roll in the extreme condition. Firstly, the EHPS system is designed to provide accurate control input of front wheel angle for vehicle lateral dynamics control. Secondly, on the basis of optimal preview theory, a new trajectory tracking fusion controller combined with sliding mode control is proposed to improve the accuracy and stability of the system in the process of vehicle lateral trajectory tracking control. Then, the stability domain boundary function of the phase plane is determined according to the phase plane of the sideslip angle-yaw rate, and the stability margin of the phase plane is calculated during the steering process. Finally, considering the tracking accuracy, lateral stability and roll stability performance in the process of trajectory tracking, the linear weighted algorithm is used to coordinate above three objectives, and the HIL bench test and real vehicle experiment verify that the proposed algorithm has good reliability and effectiveness. [ABSTRACT FROM AUTHOR]

An advanced driver-assistance system (ADAS) is critical to driver–vehicle-interaction systems. Driving behaviour modelling and control significantly improves the global performance of ADASs. A haptic assistive system assists the driver by providing a specific torque on the steering wheel according to the driving–vehicle–road profile to improve the steering control. However, the main problem is designing a compensator dealing with the high-level uncertainties in different driving scenarios with haptic driver assistance, where different personalities and diverse perceptions of drivers are considered. These differences can lead to poor driving performance if not properly accounted for. This paper focuses on designing a data-driven model-free compensator considering various driving behaviours with a haptic feedback system. A backpropagation neural network (BPNN) models driving behaviour based on real driving data (speed, acceleration, vehicle orientation, and current steering angle). Then, the genetic algorithm (GA) optimises the integral time absolute error (ITEA) function to produce the best multiple PID compensation parameters for various driving behaviours (such as speeding/braking, lane-keeping and turning), which are then utilised by the fuzzy logic to provide different driving commands. An experiment was conducted with five participants in a driving simulator. During the second experiment, seven participants drove in the simulator to evaluate the robustness of the proposed combined GA proportional-integral-derivative (PID) offline, and the fuzzy-PID controller applied online. The third experiment was conducted to validate the proposed data-driven controller. The experiment and simulation results evaluated the ITAE of the lateral displacement and yaw angle during various driving behaviours. The results validated the proposed method by significantly enhancing the driving performance. [ABSTRACT FROM AUTHOR]

Data acquisition from a vehicle operating in real driving conditions is extremely useful for analyzing the real-time behavior of the vehicle and its components. A few studies have measured the real-time data for a four-wheeler electric vehicle. However, no attempts have been reported to measure the real-time data and find the inverter efficiency for a two-wheeler electric vehicle. The present work has accomplished successful real-time data acquisition from a two-wheeler electric vehicle. The real-time current and voltage coming in and going out from the inverter, frequency of the motor operation, power factor, distance covered, and velocity have been measured. The inverter efficiency is found to be over 95% for over 80% of the total drive time, and the power factor for the motor is over 0.8 for almost 50% of the total drive time. A few insights on driver behavior and finally the torque-speed characteristics and two quadrant operation of the motor are discussed. [ABSTRACT FROM AUTHOR]

Automatic guidance of agricultural vehicles requires automatic execution of operation commands received from the navigation controller by using electronically controlled mechanisms for wheel steering, speed changing and work implementing. Automatic steering contributes as a prerequisite technique in automatic and semi-automatic agricultural navigation. This research aimed to develop an electric automatic steering system that was compact in its structure and integrated into original steering mechanism in a simply and convenient way for aftermarket modification. A brushless motor and reducer assembly was utilized to provide an adequate steering torque instead of manual maneuver. A rapid assembling approach was proposed by passing the steering shaft through the hollow output shaft. A digital proportional-integral-differential (PID) algorithm was implemented to calculate the rotation speeds and directions by comparing the desired angle and the actual angle, which was implemented in a printed circuit board with a microcontroller unit (MCU) and interface chips. An unmanned wheeled tractor was applied as test platform to integrate the newly developed electric automatic steering system. Tests were conducted to evaluate its performance in terms of stability and responsiveness. An autonomous navigation system guided the tractor along target paths in the field by sending steering commands to the electric automatic steering system. The results show that the steering angle error was less than 0.81° when desired steering angle was less than 10°. The lateral error difference was no more than 4.76 cm when repeating following the same target path, which indicated that the electric automatic steering system responded accurately and robustly to steering commands. [ABSTRACT FROM AUTHOR]

Since electric power steering has replaced hydraulic power steering in passenger cars, steering feedback has become a challenging task in steering system development. Test benches represent a valid approach for improving steering feedback since they allow investigations without the real vehicle. To improve the applicability of feedback evaluations on a steering test bench, this paper aims to identify improvements in the current evaluation technique to obtain objective parameters that correlate with a subjective evaluation of safety-relevant steering feedback. Therefore, a previously reported approach of a chirp rack force excitation, using the magnitude of the transfer function from the rack force to steering wheel torque to describe steering feedback, is compared to a similar identification approach in which a pseudo-random-binary-sequence signal is utilized. To reflect realistic applications, driving maneuvers are transferred to the test bench to identify relevant objective data. For a valid representation of the steering wheel operation, a human grip model is implemented and compared to a fixed steering wheel angle control. It is shown that the random signal represents a valid and, on average, improved approach to objectively evaluating the steering feedback. Furthermore, a recommendation can be made to include the human grip model in the feedback evaluation tests, as the identified correlation results are improved by its inclusion. The identified parameters and methods represent an improvement for future steering feedback development. [ABSTRACT FROM AUTHOR]

Accurate control of front wheel angle is essential in intelligent vehicle electric‐hydraulic power steering (EHPS) system, because it has a significant impact on the safety, comfort, and reliability of vehicle steering. However, the accurate control of front wheel angle is a challenging problem due to the non‐linearity of hydraulic power in steering system and the uncertainty of steering resistance. In this paper, a model predictive control (MPC) method for front wheel angle based on steering resistance estimation is proposed. Firstly, through theoretical analysis and practical experiment of EHPS system model, the relationship between front wheel angle and steering wheel angle and the non‐linear characteristics of hydraulic power are obtained. Secondly, a sliding mode observer is established to estimate the front axle lateral tyre force and steering resistance, which is verified by MATLAB/TruckSim co‐simulation. Then a controller based on the MPC theory is designed and applied to the accurate control unit of front wheel angle in the EHPS system for real‐time control. Finally, the simulation and test platform results show that the control algorithm proposed in this paper can precisely control the vehicle's front wheel turning angle within a certain frequency range. [ABSTRACT FROM AUTHOR]

Danfoss Power Solutions Aps has a product line focusing on hydraulic steering units for heavy-duty machines. The focus of this paper is on the end-stop torque encountered by the operator for a new asymmetrical hydraulic steering unit, referred to as sSteer. This hydraulically asymmetric concept increases the steering responsiveness between the steering wheel input and the output. However, compared to traditional hydraulic steering units, the asymmetrical design has a drawback regarding the level of end-stop torque felt by the operator when reaching the left-side end stop. This paper investigates three different concepts for improving/increasing the end-stop torque, namely, including a bleed orifice, removing a set of suction valves, and a solution with pre-tensioned suction valves and tank line. During the investigations, these concepts were compared and benchmarked using experimental data to identify advantages and disadvantages. Based on the investigations, it is concluded that the concept with pre-tensioned suction valves and a pressurized tank line ensures the best compromise between the different design requirements and the establishment of a firm end-stop feeling for the operator. [ABSTRACT FROM AUTHOR]

This research aims to investigate steering feel by analyzing a steering system and an electric power steering logic. First, steering feel is defined based on previous research, and methods for evaluating it are discussed. Second, a sensitivity analysis is conducted by modeling our developed vehicle and that of a competitor known for its excellent steering feel via a multi-body simulation. We then propose a straightforward method to determine the parameters associated with steering feel to achieve the desired steering characteristics. Last, by modifying the electric power steering control system, we achieve a steering feel in our vehicle that matches the desired steering characteristics. [ABSTRACT FROM AUTHOR]

Vehicle dynamics play an important role in determining a vehicle's stability. It is necessary to identify and obtain models related to vehicle dynamics to evaluate the performance of electric vehicles, as well as how to control them. This paper presents fundamentals of vehicle dynamics, proposing a three-degree-of-freedom nonlinear observer and controller to control lateral velocity and tire torque in comparison to a PID control, while also utilizing a Lyapunov function to determine the stability of the controlled state feedback system concerning the observer, which estimates state errors. This work demonstrates the mathematical development of estimations that will be fed into the algorithms of two active nonlinear controls (state feedback and PID), utilizing the results from Matlab-Simulink simulations of tire torque, lateral and angular velocities based on longitudinal velocity measurements, and employing dynamic gains, such as response to a steering maneuver by the driver following the international standards ISO 7401/2011 and ISO 3888-2. It is concluded that the observer is robust and exhibits energy-saving efficiency in tire torque, even under conditions of variable tire-ground friction. [ABSTRACT FROM AUTHOR]

To cope with the megatrends electrification, automated driving, and connectivity, new functionalities and electric and/or electronic systems must be developed, which require a safe power supply. This leads to increased functional safety requirements for the power supply system, particularly regarding availability. Fault tolerance measures can be implemented to comply with a safety goal (SG) specifying a safety-related availability requirement. To verify an architecture concerning the residual risk of an SG violation, several quantitative target values are provided in ISO 26262. This technical elaboration presents a systematic and holistic approach how to gain benefit in the quantitative evaluation from cyclic safety mechanisms (SMs)– in a fault tolerant item– which have a fault handling time interval (FHTI) longer than the fault tolerant time interval. Modelling cyclic SMs only based on conventional AND-gates is not sufficient. Instead, the fault sequence is differentiated to enable ISO 26262-compliance. Within this paper, an innovative approach including its mathematical background is presented how cyclic SMs can be modelled in a fault tree analysis– with focus on multiple-point faults. The results are verified by a Monte-Carlo-Simulation. Besides the scalability of the approach regarding the number of considered cyclic SMs, the relevant FHTI of each cyclic SM can be considered in a traceable and comprehensible manner.

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This paper presents an application for monitoring power systems in a Melex type vehicle. The application is intended to optimise the energy use of the modified hybrid drive system used on this vehicle. It was written in Python programming language and is used to display vehicle operating parameters on a touch screen located on the control panel. A system for monitoring voltages and currents, of the electrical part of the drive train of a Melex vehicle, was designed and built, together with a data acquisition system. Tests were carried out on the basis of the completed measuring system, a selected section of which is presented in this paper. [ABSTRACT FROM AUTHOR]

A single‐input dual‐output (SIDO) converter is proposed in the research article for usage in electric vehicle (EV) applications. The main objectives of the proposed integrated Luo‐Buck converter (ILBC) based BLDC drive system are to develop a multi‐purpose converter with low complexity and high efficiency, as well as to reach the rated speed of BLDC‐based vehicles. The multi‐output converter is generally employed in EV applications because of the primary load and extra auxiliary loads like sensors, power steering, headlights, and so on. The proposed system achieves both of the aforementioned objectives. As there are just two switches, fewer gate driver circuits are required, which indirectly lowers the complexity of the circuit. Since they do not require large duty cycles, ILBC switches experience less voltage and current stress. The switches can only be used at duty cycles of 60% and 30%. For design purposes, output filter capacitor sizes are likewise maintained to a minimum. The 1.2 kW BLDC is powered by the ILBC, which has a maximum efficiency of 96.16%, in order to validate the suggested system using the hardware prototype model. The rated speed can be attained with the least amount of timing. Additionally, the suggested approach lessens voltage and torque ripple. [ABSTRACT FROM AUTHOR]

This paper proposes a new observer approach used to simultaneously estimate both vehicle lateral and longitudinal nonlinear dynamics, as well as their unknown inputs. Based on cascade observers, this robust virtual sensor is able to more precisely estimate not only the vehicle state but also human driver external inputs and road attributes, including acceleration and brake pedal forces, steering torque, and road curvature. To overcome the observability and the interconnection issues related to the vehicle dynamics coupling characteristics, tire effort nonlinearities, and the tire–ground contact behavior during braking and acceleration, the linear-parameter-varying (LPV) interconnected unknown inputs observer (UIO) framework was used. This interconnection scheme of the proposed observer allows us to reduce the level of numerical complexity and conservatism. To deal with the nonlinearities related to the unmeasurable real-time variation in the vehicle longitudinal speed and tire slip velocities in front and rear wheels, the Takagi–Sugeno (T-S) fuzzy form was undertaken for the observer design. The input-to-state stability (ISS) of the estimation errors was exploited using Lyapunov stability arguments to allow for more relaxation and an additional robustness guarantee with respect to the disturbance term of unmeasurable nonlinearities. For the design of the LPV interconnected UIO, sufficient conditions of the ISS property were formulated as an optimization problem in terms of linear matrix inequalities (LMIs), which can be effectively solved with numerical solvers. Extensive experiments were carried out under various driving test scenarios, both in interactive simulations performed with the well-known Sherpa dynamic driving simulator, and then using the LAMIH Twingo vehicle prototype, in order to highlight the effectiveness and the validity of the proposed observer design. [ABSTRACT FROM AUTHOR]

Featured Application: The model and analysis results established in this paper can be used for dynamic analyses of the autonomous driving control of articulated steering vehicles, as well as for the design of hybrid or pure electric power articulated steering vehicles. Articulated steering vehicles (ASVs), with brilliant maneuverability and efficiency, are being widely applied in mining, construction, agriculture, and forestry. However, their special structures result in them having complex dynamic characteristics, but there are no reliable models for further research. This study established a simulation platform with the dynamic model of ASVs, where the subsystems of the power train, steering systems, tires, and frames were also included. The dynamic model was validated with field test data of typical working cycles, in which the focus was on longitudinal and lateral motions and the characteristics of steering and power train systems. Then, the distribution of hydraulic and drive power was revealed using the simulation platform and test data. For a load–haul–dump (LHD) vehicle with a 6 m3 capacity, the maximum power of the system was about 289 kW; the power of the motor accounted for the majority of the power at the beginning stage of loading, being about 74%, and then the hydraulic power dominated in the later stage of loading. During the transport stage, the power of the motor accounted for about 79% of the total power. Finally, the influence of the dynamic parameters on lateral and longitudinal motions was analyzed based on the validated platform. [ABSTRACT FROM AUTHOR]

Trajectory tracking is one of the key technologies for tractor automatic navigation. Its main purpose is to adjust the steering mechanism of the tractor to follow the planned trajectory. Thus, in this paper a trajectory tracking control system is designed for an agricultural tractor with the electric power steering mechanism. A DC brush motor is added on the steering column of the tractor and the hardware circuits for the steering controller are designed to control the front wheel angel. The three degrees of freedom model of the tractor is established, and a trajectory tracking control system is proposed including a fuzzy sliding mode controller and a steering angle tracking controller designed according to the internal mode control and minimized sensitivity theory. The effectiveness of the designed trajectory tracking control system is demonstrated by simulation analyses in reference to the planed trajectory. [ABSTRACT FROM AUTHOR]

The key problems of the steering system and vehicle handling stability of distributed drive electric vehicles are studied in the paper. According to the performance of the distributed drive electric vehicle, a seven-degree-of-freedom is established to match the parameters with the model of CarSim software. Based on the maneuverability improvement control algorithm of the active front wheel system [Active Front Steering (AFS)]/differential power steering system coupling redundancy between differential drive assist steering (DDAS), a AFS/DDAS system coordination control strategy is formulated to reduce the influence of undesirable cross-pendulum moments on vehicle stability. Through the requirements for vehicle stability, a distributed control strategy for the steering stratification of electric vehicles is developed. In the upper layer, the direct transverse moment controller is designed by the linear quadratic regulator algorithm, and the stability control area is divided into a stable region, a transition region, and an unstable region according to the center-of-mass deviation angle. Then the weights of the three subsystems are determined by judging the control area of the vehicle. The lower controller distributes the additional torque from the final calculation of the upper controller to the driving wheels through an allocation algorithm. Finally, using the CarSim/Simulink simulation platform and the dSPACE hardware-in-the-loop real-time simulation platform, the effectiveness and real-time performance of the steering coordination control strategy are verified by simulation experiments under typical working conditions, such as double shift line, step, and sinusoid. [ABSTRACT FROM AUTHOR]

In order to solve the problem where the traditional electric power steering system (EPS) provides too much assist torque under low load and low adhesion coefficient, which damages the driver's road feeling and affects driving safety, this paper designs a multi-map EPS control strategy. First, based on the change of steering resistance torque under different front axle loads and adhesion coefficients, EPS power characteristics considering the front axle load and adhesion coefficient were designed. In addition, the BP (Back Propagation, BP) neural network is used to determine steering resistance torque under different front axle loads and adhesion coefficients. Furthermore, the EPS control strategy based on multi-map is proposed. The proposed control strategy is evaluated through the co-simulation of Trucksim and Simulink. Simulation results show that the proposed EPS control strategy gives the vehicle good steering portability, with the handling torque meeting the ideal handling torque for a commercial vehicle. Under light load and low adhesion coefficient conditions, the lateral acceleration and yaw rate with traditional EPS are 0.1674 g and 5.641 deg/s, and with multi-map EPS are 0.1399 g and 4.715 deg/s. Therefore, the vehicle's handliitung stability is improved. The steering wheel torque gradient is also increased, and the driver's road feeling is improved. [ABSTRACT FROM AUTHOR]

Based on the energy policy simulation model (EPS model) and the reality of Zhejiang Province and Inner Mongolia Autonomous Region, the carbon pricing policy scenario and the early retirement policy scenario of coal power generation units were constructed, respectively, and the policy effects simulated. The study explored whether Inner Mongolia Autonomous Region can learn from the low-carbon policies that have played a good role in Zhejiang Province in the process of achieving a carbon peak. The research found that: (1) Under the baseline scenario, both Zhejiang Province and Inner Mongolia Autonomous Region failed to achieve a carbon peak by 2030. (2) Under the scenarios of carbon pricing and early retirement of coal power generation units, the peak time of carbon in Zhejiang Province and Inner Mongolia Autonomous Region has been advanced, which shows the effectiveness of carbon pricing and early retirement of coal power generation units. (3) The above two policies have achieved good results in the overall implementation process of Zhejiang Province, but the carbon pricing policy has caused dramatic fluctuations in the power generation in Inner Mongolia Autonomous Region, and the early retirement policy of coal power units has failed to achieve the goal of reaching the peak carbon in Inner Mongolia Autonomous Region on schedule. [ABSTRACT FROM AUTHOR]