Electric Power Assisted Steering Research Articles

An Examination of Component-Based TPA Performance and Feasibility for Steering Motors

The swift progression in the automotive sector has spurred the demand for electric power-assisted steering systems, heralding a transformation towards a more effortless, fluid, and pleasurable driving experience. However, the inherent generation of substantial noise levels within the vehicle’s cabin during the operation of these systems, can compromise the comfort of occupants, underscoring the criticality of acoustics analysis in the advancement of auxiliary systems. As long-established tools for Noise, Vibration, and Harshness (NVH) diagnostics, Transfer Path Analysis (TPA) techniques are central to studying noise propagation within vehicles. Component-based TPA, with its strength in identifying interface forces in mechanical structures, has gained a foothold in the industry due to its numerous advantages. We aim to shed light on the individual acoustic properties of the electric motor, thereby gaining a more nuanced understanding of the system’s behavior. We first lay out a brief theoretical background on relevant TPA methods, followed by the presentation of our findings from experimental studies. This paper continues our commitment to advancing the precision and practical use of TPA methodologies in automotive system analysis.

Efficient NVH Analysis of Electric Motors by Means of 2D Spectral Decomposition of Airgap Forces

The growing popularity of hybrid and electric vehicles has created a need for quieter electric motors. This has led to a focus on designing electric machines with reduced audible noise. Estimating the emitted noise requires complex calculations, but analyzing electromagnetic forces alone can provide valuable insights. Electric motors’ simple cylindrical structure allows for decoupling excitation forces and mode shapes, which are closely related. By representing the internal forces in a complex-valued matrix and calculating its 2D Fast Fourier Transform (FFT), we can obtain a comprehensive 2D spectrum that reveals temporal and spatial frequencies. The method enables individual analysis of unique harmonic components. This paper discusses the mathematical representation of forces, their spectra, and the relationship between force harmonics and mode shapes. Industrial examples of electric power-assisted steering systems demonstrate the practical application of this approach.

Model Reference Control-Based Steering Feel Improvement for Electric Power-Assisted Steering System

Abstract Drivers are sensitive to steering feel of a vehicle and significant tuning efforts are placed to set the desired steering feel. This paper discusses a closed-loop torque overlay control system to improve the steering feel of an electric power-assisted steering (EPAS) system. This system has reference model, rack force estimator, and tracking controller. A target steering feel is generated from a reference model in which it uses an estimate of rack force determined from a Kalman filter-based rack force estimator to reflect the actual vehicle operating conditions. A sliding mode controller is designed for tracking the target steering feel. The performance of the proposed control system is evaluated through simulation and a hardware-in-the-loop test. The simulation and experimental results show that the EPAS system with the proposed control method can successfully improve the steering feel under various operation conditions.

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.

Steering Feedback Transparency Using Rack Force Observer

The closed-loop electric power-assisted steering and steer-by-wire systems are <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">non-transparent</i> toward the environment, i.e., the tire–road interaction dynamics. To achieve driver–environment <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">transparency</i> , a rack force estimate is required. With the introduction of dynamic rack force observer feedback, a closed-loop interconnection is formed. Therefore, the driver coupled stability must be ensured with this interconnection. Consequently, an upper bound condition on transparency is derived using <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">passivity</i> for different control architectures. For selecting an observer with reasonable performance, two rack-force estimation schemes are investigated and compared, i.e., using vehicle motion signals from the inertial measurement unit sensor and the steering system sensors. Experiments indicate that the former approach has inferior performance due to vehicle inertia and signal latency, whereas in the latter approach, nonlinear estimation using second-order dynamics provides the best result; hence, it is selected to realize transparency. Finally, real-world experiments on an electric power-assisted steering vehicle illustrate the differences between non-transparent and transparent steering feedback when driving at the limits of handling on an icy road surface.

Explicit parallel co-simulation approach: analysis and improved coupling method based on H-infinity synthesis

Co-simulation is widely used in the industry for the simulation of multidomain systems. Because the coupling variables cannot be communicated continuously, the co-simulation results can be unstable and inaccurate, especially when an explicit parallel approach is applied. To address this issue, new coupling methods to improve the stability and accuracy have been developed in recent years. However, the assessment of their performance is sometimes not straightforward or is even impossible owing to the case-dependent effect. The selection of the coupling method and its tuning cannot be performed before running the co-simulation, especially with a time-varying system.In this work, the co-simulation system is analyzed in the frequency domain as a sampled-data interconnection. Then a new coupling method based on the H-infinity synthesis is developed. The method intends to reconstruct the coupling variable by adding a compensator and smoother at the interface and to minimize the error from the sample-hold process. A convergence analysis in the frequency domain shows that the coupling error can be reduced in a wide frequency range, which implies good robustness. The new method is verified using two co-simulation cases. The first case is a dual mass–spring–damper system with random parameters and the second case is a co-simulation of a multibody dynamic (MBD) vehicle model and an electric power-assisted steering (EPAS) system model. Experimental results show that the method can improve the stability and accuracy, which enables a larger communication step to speed up the explicit parallel co-simulation.

EPAS Fail-Safe Control using Differential Braking

One of the main systems for ground vehicles is the Electric Power Assisted Steering (EPAS). Due to its importance, a redundant system is usually implemented. This solution remain however expensive, especially for small urban cars. This paper proposes an alternative fail-safe control algorithm using this time differential braking. Controlling each brake apart generates a yaw moment enabling turning the vehicle. Optimal coordination is ensured due to the importance of this maneuver. Results show that differential braking, that already exist in most of passenger cars, is able to generate a sufficient additional yaw moment to help the driver steer his/her vehicle. This can reduce the space and the cost of the vehicle.

Design of a Parameterized Model Predictive Control for Electric Power Assisted Steering

Electric Power Assisted Steering (EPAS) enables better driver’s steering and user experience. It plays an important role for ADAS and automated driving (AD) features. EPAS control strategies are still in infancy entailing continuous monitoring and driver intervention. In fact, EPAS solutions have required more fail-safe strategies and optimal control algorithms for dynamics and road conditions. This paper presents a novel EPAS control strategy based on the parameterized Model Predictive Control (MPC) technique. The parameterized MPC scheme provides low computation effort enabling real-time implementation of the proposed control strategy. Experimental results highlighted success on tracking desired assistant torque without violating predefined operating constraints.

Modeling Static Load Distribution and Friction of Ball Bearings and BNAs: Towards Understanding the “Stick-Slip” of Rack EPAS

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Electric power assisted steering (EPAS) systems are widely adopted in modern vehicles to reduce the steering effort of drivers. In rack EPAS, assist torque is applied by a motor and transmitted through two key mechanical components: ball bearing and ball nut assembly (BNA) to turn the front wheels. Large combined load and manufacturing errors not only make it hard to accurately calculate the load distribution in the ball bearing and BNA for the purpose of sizing, but also make the friction behavior of EPAS gear complicated. Rack EPAS gear is well known to suffer from “stick-slip” (i.e., sticky feel sensed by the driver), which affects the user experience. “Stick-slip” is an extreme case of friction variation mainly coming from ball bearing and BNA. Finite Element Analysis (FEA) in commercial software like ANSYS is usually conducted to study the load distribution and friction of ball bearing and BNA. However, conducting FEA using commercial software is time consuming and does not offer fundamental understanding. The authors of this paper have developed and validated low-order static load distribution model and ball-to-ball contact friction model in their prior works. In this paper, the applications of the proposed models to EPAS are shown. Using the developed static load distribution model, axial and conical lash tests are compared; the effect of geometric errors on load distribution of BNA is studied. The developed static load distribution model proves to be useful for the sizing of ball bearing and BNA in EPAS. On the other hand, the friction behavior of BNA incorporating ball-to-ball contact is simulated to illustrate the “stick-slip” phenomenon. The developed models are thus shown to be very useful analytical design verification tools of ball bearings and BNAs in EPAS.&lt;/div&gt;&lt;/div&gt;

Development of Safe and Sustainable EPAS (Electric Power Assist Steering) System for Emerging Markets

Development of Safe and Sustainable EPAS (Electric Power Assist Steering) System for Emerging Markets

Study on parameters affecting steering feel of column assist electric power steering

In recent years, the electric power assist steering (EPAS) system, because of its fuel efficiency, cost effectiveness, and additional safety and convenience features, has rapidly replaced the conventional hydraulic power assist steering (HPAS) system. However, there is still need for improvement of the steering feel of EPAS systems compared to HPAS systems. In this paper, the steering feel of the EPAS system is studied by investigating the steering feel metrics. We first introduce a comprehensive model of a column-assisted EPAS (C-EPAS) system consisting of the major components in the system. The steering feel of the C-EPAS system is then investigated through simulation of on-centre steering tests based on the proposed mechanical model with basic power assist control strategies. Various factors affecting the steering feel responses are identified. Finally, by using this knowledge, it is shown that on-centre steering feel can be improved by adjusting the proper parameters in the C-EPAS system.

Robust steering-assist torque control of electric-power-assisted-steering systems for target steering wheel torque tracking

This paper describes robust steering assist torque control of electric-power-assisted-steering (EPAS) systems for a target steering wheel torque tracking. The steering assist torque control algorithm has been developed to overcome the major disadvantage of the conventional method of time-consuming tuning to achieve the desired steering feel. A reference steering wheel torque map was designed by post-processing data obtained from target performance vehicle tests with a highly-rated steering feel for both sinusoidal and transition steering inputs. Adaptive sliding-mode control was adopted to ensure robustness against uncertainty in the steering system, and the equivalent moment of inertia damping coefficient and effective compliance were adapted to improve tracking performance. Effective compliance played a role in compensating the error between the nominal rack force and the actual rack force. The performance of the proposed controller was evaluated by conducting computer simulations and a hardware-in-the-loop simulation (HILS) under various steering conditions. Optimal steering wheel torque tracking performances were successfully achieved by the proposed EPAS control algorithm.

Vehicle side-slip angle estimation on a banked and low-friction road

The effective application of integrated vehicle dynamics control and automatic driving require consistent vehicle state variables and parameters. Considering lateral vehicle dynamics, the yaw rate and (estimated) vehicle side-slip angle are the minimum set of state variables that can give insight into the handling characteristics of a vehicle. Various methods of vehicle side-slip angle (lateral velocity) estimation have been tested in virtual and real world applications, in particular on a horizontal dry road. Vehicle side-slip angle, however, is not only affected by the (steering) commands of the driver, and possibly by a vehicle dynamics controller, but can also arise from a banked road or result from a low-friction surface, changing tyre–road contact. The combined effects require a comprehensive estimation approach, which is less often touched upon in the literature. Based on earlier findings on important aspects of observability, the paper addresses a modular vehicle side-slip angle estimation approach that is particularly focused upon practical aspects of modelling and design. Estimation of the combined vehicle side-slip angle, road bank angle and maximum tyre–road friction coefficient has been broadly tested with a vehicle equipped with an electronic stability control (ESC) and electric power-assisted steering (EPS) sensor configuration, for various road conditions, driving situations and vehicle/tyre setups.

Investigation of the Driver’s Arm Viscoelastic Properties During Steering Vehicle Maneuver

Driver's arm viscoelastic properties during steering vehicle maneuver are very important information to understand how the driver regulates his torque and they could be used to design a new driver assistance system. This correspondence paper investigates the driver's arm viscoelastic properties during steering vehicle maneuver. First, a time-varying method for estimating driver's arm viscoelastic properties during driving the vehicle is proposed. Then, this method is implemented experimentally in order to examine the driver's arm viscoelastic properties during driving the vehicle. The estimation method does not require a specific perturbation torque to be applied during driving and could be applied online. The method is based on a time-varying model of the human driver's arm coupled with the electric power-assisted steering system model. Experiments were carried out with five healthy subjects who drove on a hardware-in-the-loop simulator without assistance and with assistance.

Energy Optimization of Brushed DC Motor in Electric Power-Assisted Steering

Electric power-assisted steering (EPS) is a control system where an electric motor is used to provide assistance in vehicle steering. In this work controllers are designed for a column-type EPS equipped with a brushed DC motor to enable energy optimization. Using a mathematical model of EPS a controller is developed based on nonlinear adaptive regulation method to generate driver torque. PID control is then applied to produce assistance torque in accordance to desired energy saving. Simulation results using Matlab show the trade-off between driver’s comfort and energy consumption. The control paradigm introduced here fits appropriately in electric vehicles (EVs) where electrical energy is scarce.

Energy Optimization of Brushless DC Motor in Electric Power-Assisted Steering

In an electric power-assisted steering (EPS) an electric motor is controlled to provide assistance in vehicle steering and to enable various steering feels. To optimize energy consumed by a column-type EPS equipped with a brushless dc (BLDC) motor the author designs two controllers as needed. Firstly a controller to generate driver torque is developed based on nonlinear adaptive regulation method using the mathematical model of EPS. The second controller is a PID motor controller that is applied to produce assistance torque for desired energy saving. The trade-off between driver’s comfort and energy consumption is demonstrated using Matlab simulation results. In electric vehicles (EVs) where electrical energy is limited the control scheme introduced here is expected to fit perfectly.

Self-Alignment Torque as a Source of Energy Recovery for Hybrid Electric Trucks

This paper describes a new function for electrical-power-assisted steering (EPAS) systems applied for hybrid electric trucks (HETs). EPAS systems consume power to provide torque to steer the wheels. The required power must be equal to the power caused by the self-alignment torque that forces the wheels back into the aligned position. This paper describes, for the first time, how self-alignment torque is used to recover energy that is required to turn the wheels. This paper shows that, for a common steering maneuver, a maximum of 20% of the energy required to complete the steering maneuver can be recovered. This energy saving relates to a fuel gain of 2094.5 gal over the lifetime of a truck of 500 000 mi. This paper also shows that the new EPAS function can be embedded in existing systems without changes to the hardware or the motor configuration. An EPAS model is developed in Dymola to show how steering at various vehicle speeds and various steering wheel angles contribute to the energy savings. An EPAS drive has been designed, constructed, and tested for an HET to validate the simulation results.

Research on the PID Tuning of Electric Power-Assisted Steering Test Bench System

Electric power-assisted steering(EPAS) bench system can be used for fatigue and functional testing of automotive steering .To get a better performance and higher precision of EPAS system, theory analysis and simulation about passive loading system is carried out in this paper. A new strategy combined particle swarm optimization with PID algorithm is put forward to solve the shortcomings of traditional method. Simulations in different methods show the effectiveness of it.

Hybrid PID and PSO-based control for electric power assist steering system for electric vehicle

Electric power assist steering (EPAS) system provides an important significance in enhancing the driving performance of a vehicle with its energy-conserving features. This paper presents a hybrid PID (Proportional-Integral-Derivative) and particle swarm optimization (PSO) based control scheme to minimize energy consumption for EPAS. This single objective optimization scheme is realized using the PSO technique in searching for best gain parameters of the PID controller. The fast tuning feature of this optimum PID controller produced high-quality solutions. Simulation results show the performance and effectiveness of the hybrid PSO-PID based controller as opposed to the conventional PID controller.

Optimisation of energy in electric power-assisted steering systems

Electric power–assisted steering (EPS) is a control system where an electric motor is used to provide assistance in vehicle steering. In this work controllers are designed for column–type EPS systems to enable energy optimisation. Two EPS systems are considered, namely brushed DC motor equipped EPS and brushless DC (BLDC) motor equipped EPS. Using mathematical models of EPS controllers are developed based on nonlinear adaptive regulation method to generate driver torque. Proportional–Integral–Derivative (PID) control is then applied to produce assistance torque in accordance to desired energy saving. Simulation results using Matlab show the trade–off between drivers comfort and energy consumption. The control paradigm introduced here fits appropriately in electric vehicles (EVs) where electrical energy is scarce.