Electric Power Steering System Research Articles

Research on active disturbance rejection control strategy of electric power steering system under extreme working conditions

In response to the influence of motor interference, damping, friction, and other uncertain factors on the operation of electric power steering systems under extreme working conditions, this study proposes a control strategy for electric power steering systems based on an active disturbance rejection algorithm. In ADRC, the fastest tracking differentiator is used to arrange the transition process for the target signal, and the extended state observer compensates for the total disturbance in the system. Phase compensation has been performed on the monitoring torque by using the torque differentiation method. The Simulink/Carsim simulation results show that ADRC has significantly improved anti-disturbance performance compared to PID and fuzzy PID. When using ADRC, the tracking accuracy of the assisted current is enhanced by 45.8%–75.8%, and the current adjustment time is reduced by 35.6%–61.7%. After phase compensation, the monitoring torque overshoot is reduced by 83.3%. Therefore, the proposed control strategy improves EPS’s robustness and steering feel.

IoT-Driven Parking System: Integrating 4WD, 4WS, And Parking Sensors for Electric Four Wheelers' Enhanced Maneuverability

Innovative automotive technologies like 4-Wheel Drive, 4-Wheel Steering, and Electric Power Steering systems can greatly enhance a vehicle's performance, stability, and handling. These technologies are commonly found in high-end vehicles due to their ability to improve traction, maneuverability, and steering accuracy. A sophisticated system utilizing a combination of advanced sensors, electronic controls, and mechanical components would enable each wheel to turn independently of the others. Such a system could provide even better handling, stability, and traction in challenging driving situations. The integration of independent wheel turning mechanisms, 4-Wheel Drive, 4Wheel Steering, and Electric Power Steering has the potential to transform the automotive industry, offering enhanced safety and efficiency in addition to providing an enjoyable driving experience, making it more appealing to drivers.

Neural Approximation-Based Adaptive Control Using Reinforced Gain for Steering Wheel Torque Tracking of Electric Power Steering System

In practice, steering wheel torque (SWT) control performance for an electric power steering (EPS) system may degrade owing to various reasons, such as model/parameter uncertainties and unpredictable large external disturbances (e.g., reaction force). Furthermore, the desired SWT suddenly varies and its sign also changes because the direction of the steering wheel angle (SWA) often changes according to the driver. In this article, a neural network (NN) approximation-based adaptive nonlinear control (ANC) using reinforced gain (RG) for an EPS system is proposed to resolve the above-mentioned problems using an SWT model. The proposed control method employs an NN approximator, ANC, and RG. The NN approximator is designed to estimate the unknown complex nonlinear function in EPS modeling. The ANC is designed via backstepping to compensate for parametric uncertainties and external disturbances. Further, the RG is designed as a positive nonlinear function of the error to sufficiently suppress the error according to variations in the desired SWT and external disturbance. The RG increases to suppress the error at a rapid transient response, owing to the sudden change in the sign of the desired SWT and the external disturbance. Thus, a high gain (increased RG) is used only when necessary so that an unnecessarily high gain can be avoided.

Robust Nonlinear Torque Control Using Steering Wheel Torque Model for Electric Power Steering System

In this paper, a robust nonlinear torque control method using the steering wheel torque (SWT) model is proposed for electric power steering (EPS) systems. We develop an EPS model using SWT as the state variable to directly control the SWT. A robust nonlinear torque control method is designed to improve the SWT control performance of EPS. The proposed method consists of an extended state observer and a nonlinear sliding mode control (SMC) method. The extended state observer is designed to estimate the lumped disturbance, which includes modeling errors and external disturbances for robustness. The SMC is designed to track the desired SWT and suppress the estimation error. The nonlinear gain is proposed for reducing the chattering in the SMC. The proposed method is designed based on the SWT model; thus, it can improve the torque control performance while remaining robust to parameter uncertainty and external disturbances. The performance of the proposed method is validated via experiments using a pinion type EPS hardware-in-the-loop simulation.

Linear assistance filter design for electric power steering systems with improved delay margin

This paper studies the achievable delay margin using lead-lag filter structures for Electric Power Steering systems. We propose an approximation of the delay margin as an explicit function of filter parameters. Our results provide useful guidelines for adjusting the different filter parameters to ensure system stability in the presence of a time delay. Simulation results show that the proposed filter structures can attenuate vibrations and improve steering feel and road feel. As a consequence, the influence of the delay on the system can be minimised with little performance degradation.

Power Electronics Converters for Electric Vehicle Auxiliaries: State of the Art and Future Trends

Electric vehicles (EVs) are expected to take over the transportation and mobility market over traditional internal combustion engine (ICE) vehicles soon. The internal power demands of EVs are expected to increase. The reason for this is to achieve a longer driving range for the EV and to provide the required power for the low-voltage (LV) network auxiliary loads. To illustrate, there are extra added sensors, cameras, and small actuating motors, especially for future autonomous vehicles. Therefore, a new electrical/electronic (E/E) architecture is required to convert the high-voltage (HV) traction battery voltage (e.g., 320–800 V DC) to the standard LV levels with high current ratings of 5 kW and more. This HV-LV DC-DC converter is known in the literature as an auxiliary power module (APM). The standard LV rails in an EV are the 12 V/24 V rail to supply for an instant the EV’s lighting and electronic control units (ECUs), while the 48 V rail is required for propulsive loads, such as air compressors and electric power steering systems. Furthermore, in a few applications, this converter is responsible for voltage upwards to support the start of a hybrid vehicle or emergency backup power handling, which requires bidirectional capability. Therefore, in this paper, possible APM topologies for EV applications are presented. In line with this, the main standards and safety requirements of the APMs are presented. Detailed quantitative and qualitative comparisons between topologies and their associated control schemes are discussed. In addition, the placement of the APM in the EV cooling cycle has been investigated and demonstrated. Finally, the industrial trends and future research targets for the APM in automotive applications are outlined.

Study on Control Strategy of Electric Power Steering for Commercial Vehicle Based on Multi-Map

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.

Speed Response Improvement Design of Electric Motor for Vehicle Electrification Based on Electro-Mechanical Analytic Model

According to vehicle electrification trends, the application of electric motors more often occurs. Therefore, in the aspect of the supply instability preparation for rare-earth materials, research on the rare-earth-free motor is getting more attention. Moreover, the electric motor for the vehicles should have not only high power density but also fast response. Especially, electric motors for advanced driver assistant systems (ADAS) or autonomous driving vehicles should have a fast response speed to secure the driver’s safety. This paper introduces the electro-mechanical response improvement design of concentrated flux synchronous motors for vehicle electrification. Improvement design is carried out targeting motors for electric power steering (EPS) system. The development of the electro-mechanical analytic (MEA) model of the electric motor is firstly explained. Then, based on the developed MEA model, electro-mechanical response modeling is performed. Finally, the speed response improvement design is conducted using the developed MEA model. In addition, the results are validated not only in finite element analysis but also experimentally.

Fault Estimation of Rack-Driving Motor in Electrical Power Steering System Using an Artificial Neural Network Observer

In this paper, we present the fault estimation of a motor in rack-type electrical power steering (R-EPS) system using an artificial neural network (ANN) observer and the comparison study of estimation performance between ANN observer and model-based ones. For various amplitudes and frequencies of fault, it is not easy to obtain the accurate fault estimation using the model-based observers inherently possessing the accumulated errors and disturbance effect. Such model-based methods often result in undesired consequences; hence, this study employed the “model-free” ANN observer, without using any dynamics and parameters of a motor, to accomplish the better outcomes. Furthermore, the advantages of ANN observer for the fault estimation of the motor have been clearly investigated under several control/fault scenarios, and the effectiveness of proposed work has been validated through an actual experimental study. It is found that the performance of model-based approaches is degraded when the frequencies and amplitudes of fault and control scenarios are changed, but the ANN observer guaranteed performance that was almost the same regardless of fault and control scenarios. Notably, ANN observers showed 84% to 95% of estimation accuracy with almost no delay between estimates and actual faults while model-based approaches did 68% to 86% accuracy along with noticeable delay.

Design and analysis of electric power-assisted steering in vehicles for mountain forests

This study investigates the problem of vehicle exploitation in the mountainous and wooded regions of the Russian Federation. Considering how critical rollover accidents are in the logging industry, it is vital to ensure safe and stable driving. This study aims to develop a model of electric power steering (EPS) control using a quasi-continuous sliding-mode controller in MATLAB/Simulink. Experiments were carried out under the following conditions: maximum slope angle, 30°; maximum steering angle, 30°; maximum driving speed, 7 m/s. The dynamic characteristics of the suspension and EPS systems were optimized using the receding horizon optimization technique. The theoretical and experimental results suggest that the model reaches its critical state of stability (−0.2) at a speed range of 0–7 m/s with a steering angle of 25°. After optimization, critical stability (0.3) occurs at the driving speed of 7 m/s when the steering angle is 30°. The paper discussed the possibility of installing the EPS control system into vehicles that operate in mountainous wooded areas.

Simulation and application of the electric power steering system simulation platform based on Simulink

The principle of the electric power steering system is introduced in this paper, and the simulation platform based on Simulink/Simscape is established. The mechanical structure of the steering gear, the timing scheduling strategy, the hardware control circuit, and the integration of the software control algorithm are modeled and verified in detail. It is proved that the simulation model is reliable and highly precise. The simulation platform is used to analyze the actual problems, and propose an improvement plan. The results show that the platform can improve the intelligence of development and quickly locate, effectively reproduce and analyze actual problems, and reduce the trial-produce cost of the early production line, which has a certain guiding significance for software and hardware development.

A Deep Learning Approach to Detect Anomalies in an Electric Power Steering System.

As anomaly detection for electrical power steering (EPS) systems has been centralized using model- and knowledge-based approaches, EPS system have become complex and more sophisticated, thereby requiring enhanced reliability and safety. Since most current detection methods rely on prior knowledge, it is difficult to identify new or previously unknown anomalies. In this paper, we propose a deep learning approach that consists of a two-stage process using an autoencoder and long short-term memory (LSTM) to detect anomalies in EPS sensor data. First, we train our model on EPS data by employing an autoencoder to extract features and compress them into a latent representation. The compressed features are fed into the LSTM network to capture any correlated dependencies between features, which are then reconstructed as output. An anomaly score is used to detect anomalies based on the reconstruction loss of the output. The effectiveness of our proposed approach is demonstrated by collecting sample data from an experiment using an EPS test jig. The comparison results indicate that our proposed model performs better in detecting anomalies, with an accuracy of 0.99 and a higher area under the receiver operating characteristic curve than other methods providing a valuable tool for anomaly detection in EPS.

The control strategy of the electric power steering system for steering feel control

The steering feel is mostly indirectly adjusted by directly modifying the assist’s magnitude of the electric power steering system. The adjustment is complex, and workload is large, and the steering feel is highly dependent on the performance of the hardware. It has poor robustness to vehicle performance degradation and external disturbance, so providing a consistent and controllable steering feel is not easy. This paper proposes an EPS control strategy for steering feel control based on closed-loop control of steering motion to solve the above problems. Firstly, take the driver’s desired steering motion intensity and pinion angle position as intermediate variables to decompose the EPS control strategy into three parts: steering style, the desired pinion angle calculation, and the desired steering resistance moment calculation. This decomposition method makes the steering feel control independent of the vehicle dynamics characteristics and reduces the difficulty of vehicle characteristic calibration and correction. In addition, a steering style model based on Stevens’ law and considering hysteresis characteristics is proposed. The steering feel can be directly controlled based on calibrating the vehicle's dynamic characteristics and the designed steering style. The test results driven by ACSL driving simulators of Jilin University show that adopting the control strategy proposed in this paper can improve the vehicle’s return-to-center performance, realize the designed driving style, and provide consistent and controllable steering feel with the design hysteresis characteristic. In addition, it has good robustness against the deterioration of vehicle hardware performance and external disturbance.

Path Planning and Path Tracking for Collision Avoidance of Autonomous Ground Vehicles

How to plan the collision-free path effectively is crucial for autonomous ground vehicles to avoid collisions. The vehicle may lose its lateral dynamic stability due to high speed, time-varying speed and multifriction road during tracking the collision-free path. In this article, an advanced collision avoidance framework is proposed to avoid collision efficiently with road friction estimation and dynamic stability control. First, an improved A* algorithm is constructed to generate a desired trajectory for collision avoidance, which is capable of observing road regulations and overcoming the vehicle mechanical drawbacks. Next, a model predictive control-based path-tracking controller is established to solve the tracking task as a multiconstraint and multitarget optimization problem, where optimized steering angle and additional yaw moment can be calculated. Meanwhile, a novel long short-term memory based road friction coefficient estimator is built to observe road friction. Moreover, electric power steering system controls the steering motor to realize the desired steering angle. The additional yaw moment can be obtained by differential braking. Finally, hardware-in-the-loop platform tests are conducted to validate that the proposed controller can not only avoid collisions effectively, but also have a good performance on keeping the vehicle dynamic stability with accurate road friction estimation.

Road Torque Modeling for Electric Power Steering Systems

Road Torque Modeling for Electric Power Steering Systems

On the Analysis and Torque Enhancement of Flux-Switching Permanent Magnet Machines in Electric Power Steering Systems

Modern road vehicles are more and more often being equipped with electric actuators. These are intended to play critical roles in passengers comfort and safety. Among the electrified components onboard road vehicles, one can distinguish electric power steering (EPS) systems, which have been the subject of intensive investigations covering both design and control aspects. The abilities of several AC motor topologies to fulfil the EPS systems’ requirements have been assessed by a large scientific community in both academia and industry. The present work was aimed at the prediction of the electromagnetic features of the flux-switching permanent magnet machines (FSPMMs), with an emphasis on the air gap flux density. The latter was firstly formulated while neglecting the slotting effect at both sides of the air gap. Then, stator and rotor permeance functions, taking into account the slotting effect and the PM flux concentrating arrangement, were incorporated into the derived flux density spatial repartition. Moreover, the accuracy of the latter was improved through two dedicated correction functions that take into account the rotor position and the magnetic saturation. The last part of the paper presents a simple approach to enhance the developed torque of FSPMMs in an attempt to meet the EPS requirements.

Harmonic Order Analysis of Cogging Torque for Interior Permanent Magnet Synchronous Motor Considering Manufacturing Disturbances

This paper is a study of unintended cogging torque for the IPMSM (Internal Permanent Magnet Synchronous Motor) of an EPS (Electric Power Steering) system considering manufacturing disturbances. The IPMSM has been used recently in EPS systems with high power density. However, due to the complex rotor shape of the IPMSM, considering manufacturing disturbances, it is expected to reduce the quality of IPMSM performance. Therefore, the unintended cogging torque for motor quality is also expected to increase. This paper analyzes the causes of unintended cogging torque in the IPMSM of an EPS system considering manufacturing disturbances. Based on the harmonic order analysis of measured cogging torque for the IPMSM prototypes, the causes of unintended cogging torque in the IPMSM are verified due to the manufacturing disturbances.

극 슬롯 조합에 따른 영구자석 표면 부착형 동기전동기의 특성 분석 연구

In this paper, the characteristics of SPMSM (Surface mounted Permanent Magnet Synchronous Motor) applied to EPS(Electric Power Steering) systems were analyzed according to the combination of pole slots. In general, fractional-slot permanent magnet synchronous motors using concentrated windings have advantages such as being more economical than distributed windings, having shorter end windings, and high copper fill factor. However, traditional permanent magnet synchronous motor having the fractional slot has a relatively low winding factor due to the slot pitch and pole pitch ratio. One way to compensate for this is to use a modular motor with fewer slots for a given number of poles. The modular motor is a motor with the number of slots per pole per phase less than 0.5, and the winding factor is larger than that of the traditional motor. Therefore, in this paper, three types of motors: fractional slot modular motors, traditional motors, and integer slot motors, were analyzed and the power characteristics were compared using the FEM(Finite Element method).

Diagnosis and analysis of electric power steering rattle noise based on multiple coherence method

Electric power steering (EPS) system is becoming the primary source of Electric Vehicle (EV) noise due to absence of classic power train. The rattle noise produced by EPS, which is easily discernible when driving. Since the conventional subjective evaluation approach makes it difficult to identify the source, it is required to establish an objective way to solve such an issue. In this paper, the principle of multiple coherence method is first addressed analytically, and then is employed to analyze the vibration signal acquisition from EPS different points, meanwhile, combine with in-car sound signal, to accurately identify the specific location.

Integrated optimization design of electric power steering and suspension systems based on hierarchical coordination optimization method

Integrated optimization design of electric power steering and suspension systems based on hierarchical coordination optimization method