Research on Vehicle Chassis Integrated Control Technology Based on Coordination Strategy

The ability to avoid lane departure has become an important feature for development of driving assistance technology, and the design of lane departure avoidance system (LDAS) which can achieve cooperative control with human driver is still a challenge. This paper presented a new lane departure decision algorithm along with main parameters of the electric power steering (EPS) and electronic stability program (ESP) system’s sensor. During normal situations, steering control based on EPS system was involved to avoid lane departure. However, when the vehicle reached the handling limits, both steering and braking control collaborated together to avoid lane departure based on EPS and ESP systems. Due to the time varying vehicle speed and the uncertainty of tire cornering stiffness, a gain scheduling brake controller was designed based on the energy-to-peak performance indicator, and an upper monitor was designed for activation the braking controller to ensure comfortable ride. Because the relationship between the lane departure degree with a lateral offset in the single- point preview and the driver torque could not be accurately described, a man-machine cooperative control fuzzy observer for the LDAS was designed. In order to accomplish smooth switching for driving mode to ensure ride comfort, a switching criterion was proposed. The proposed method was evaluated via numerical simulation by CarSim/Simulink. A hardware-in-the-loop test platform was set up, and the effectiveness of the proposed control strategy was compared via the driver-in-the-loop experiment. The obtained results show that the proposed man-machine cooperative control strategy not only can return the vehicle to the normal lane effectively, but also realize smooth switching from man-machine cooperative control to driver control.

A novel electric power steering system (EPS) integrated with active front steering (AFS) is developed. It has functions of both AFS system and EPS system with two actuator units: the AFS actuator unit and the EPS actuator unit. The AFS actuator unit controls the displacement transfer behavior of the steering system, and improves the handling stability under adverse road conditions by varying the steering ratio directly related to the speed and road conditions. The EPS actuator unit controls the force transfer behavior of the steering system, and improves the steering portability and road feel of the vehicle. Based on a dynamic model, the mixed H2/H∞ control strategy of the EPS actuator and the active steering intervention control strategy of the AFS actuator are designed. The simulation indicates that the novel EPS system with the designed control strategies has obvious advantages in vehicle handling stability and the driver’s road feel over the traditional EPS system, and extends the vehicle’s steering performance.

The passive suspension system based on centralized hydraulic sources suffers from prominent issues such as large space occupancy, low energy efficiency, maintenance difficulties, and insufficient overall performance. To address these issues, this paper innovatively proposes design solutions and control strategies for multiple suspension systems based on distributed hydraulic sources, specifically tailored for heavy-duty special wheeled vehicles. A semi-active suspension system is developed based on both PID control strategy and sky-hook control strategy, which enhances suspension performance under the constraints of limited cost and minimal structural changes. A detailed comprehensive performance simulation model is established, and simulation analysis is conducted under different driving states and road surface conditions. The results indicate that the PID control strategy performs better under dynamic operating conditions such as curves, acceleration, and braking, while the sky-hook control strategy performs better when the vehicle traverses on Class C-F road surfaces. To further enhance the suspension system's performance, active and slow-active suspension systems are designed. By actively applying control forces, the limitations of the semi-active suspension, which can only respond passively, are overcome. Through the integration of road surface recognition technology, the systems can sense the road surface conditions ahead in real time and convert them into control commands in a feedforward form. This significantly improves the dynamic performance of the suspension system and reduces the performance requirements on posture stabilization devices for onboard weapons and other equipment. In terms of vehicle body deflection, vehicle body acceleration, and dynamic tire load, the relevant indicators for the active suspension are reduced to 2.5%, 7.2%, and 7.3% of those for the semi-active suspension, respectively, while the relevant indicators for the slow-active suspension are reduced to 46.3%, 31.4%, and 31.5% of those for the semi-active suspension, respectively.

To solve the power limitation problem faced by the development of EPS system for commercial vehicles and achieve the high-performance steering, this article presents a novel dual power-driven electric power steering system (DPEPS) for commercial vehicles by using the open winding permanent magnet synchronous motor (OPMSM) fed by dual inverter with high and low DC voltage supplies. First, the two-level control strategy is introduced for the developed DPEPS system, where the upper control is designed to make the actual steering follow the expected steering performance as determined by the assistant torque curve and to generate the appropriate target current according to the vehicle speed and steering torque. And then the lower control consists of the synthetical space vector control scheme and dual PI control loop is used to execute commands from the upper control, which can make the motor execute the appropriate power supply method according to the steering torque and assist current. Finally, a co-simulation model is carried out for an electric bus, and based on which the proposed DPEPS system is validated.

This study attempts to improve the vibration isolation performance of a vehicle suspension system with a magnetorheological damper (MRD) under complex driving conditions. Structure parameter uncertainty, disturbance of the driving process, and response time delay of MRD are all addressed. Firstly, experiments of MRD were carried out in a damping force testing machine to identify the parameters of the MRD adjustable Sigmoid model by the Levenberg-Marquardt optimization algorithm. Then, the parameter identification is verified by comparing experimental and simulation data. Secondly, the state space equations of the suspension system are derived by Newton’s second law. The transfer function from the bounded disturbance input to the control output is obtained based on H∞ control theory. To make the Infinite norm of the system transfer function less than a certain value, three control strategies are proposed: variable structure control (VSC), disturbance rejection control (DRC), and delay tolerance control (DTC). Thirdly, considering these issues together to weaken the effect of disturbances on vehicle driving conditions, a fuzzy cooperative control (FCC) strategy is proposed based on the linear matrix inequality (LMI) theory. Simulation results demonstrate that FCC semi-active vehicle suspension systems conduct effective vibration isolation performance while responding to multiple external disturbances.

Suspension system is used to fulfil the criteria of ride comfort and road handling. In this paper, a quarter car active & semi-active suspension systems are designed using Matlab/Script software. Comparison of active & semi-active suspension systems are done using robust control theory for the control targets suspension deflection, body acceleration and body travel. H infinity controller is selected to compare the two suspensions using time domain analysis. Finally the simulation result prove the effectiveness of the active suspension system by decreasing the body acceleration & sustaining the suspension deflection and body travel outputs.

Based on linear motor and hydraulic hybrid energy reclaiming suspension, control strategy for multi-mode switched active suspension is designed. By establishing a quarter vehicle suspension system model, a fuzzy sliding mode controller is designed to control the active suspension system, and design active suspension mode switching strategy to select and switch suspension modes of vehicles under different conditions, it improves the performance of active suspension as well as the feed-ability of the suspension. The accuracy of the model and control strategy is verified by simulation, at the same time, a quarter suspension bench is built for test. The test results show the effectiveness of the simulation. The energy-feed test shows that the energy-feed efficiency of the designed energy reclaiming suspension can reach 17.54%.

Relative to the passive suspension, automotive active suspension car driving more ride comfort and stability, has a vital role to further improve the performance of the vehicle. For such a typically complex active suspension system research, the key issue is the selection of control strategies. The problems in the currently active suspension control strategy, the principle of a simple, effective, this paper, a single neuron PID control strategy used in the automotive active suspension system. The results show that compared with other control strategies, single neuron PID control strategy is reliable, has more advantages.

Active and semi-active suspension systems are widely diffused into the automotive industry and several control strategies have been proposed in the literature both concerning ride comfort and handling. The capability of several suspension active control systems in enhancing the vehicle handling performances are compared in this paper. In particular, a low-bandwidth active suspension (actuator in series with the suspension spring), an active antiroll bar, an active camber suspension and a semi-active high-bandwidth suspension (closed loop damper control) are considered. The benchmark is represented by an ideal vehicle which does not present any load transfer and has no yaw moment of inertia. The possibility of combining more than one active/semi-active suspension system is also discussed.

Ride comfort and handling qualities of a vehicle have attained much attention in the field of automobile. Vehicle manufacturers are trying to introduce as much ride comfort as possible without compromising handling qualities of vehicle. The two characteristics of the vehicle are linked with suspension system of vehicle. Good ride comfort means that the suspension system does not let road disturbance to reach the body of vehicle, while good handling qualities implies good road grip and maneuverability of the vehicle. Main objective to improve ride comfort is to elude physical fatigue and tiredness of driver while improvement in handling qualities will minimize chance of road accidents. Different suspension systems like passive, semi-active and active have been studied for long. Semi-active suspension system can provide change in damping coefficient to fulfill requirements of a good suspension system in a simple, easy and cost-effective way without requiring change in vehicle. Therefore, semi-active damper systems have gained more popularity in automobiles field. Designing control algorithm for semi-active suspension system is a complicated and challenging task. There have been many control algorithms to control damping coefficient, but no algorithm has utilized semi-active dampers to their full potential. This study investigates shortcomings of existing approaches, root cause of the problems and provides optimal solution to the problem. A suspension system involves different regions of operations that can be separated on the bases of operational constraints and stability of system. Existing methods do not use stability for designing their controllers or separating different regions. Furthermore, existing control strategies are based on linearized models and require gain adjustment and tuning to get better performance. Through analysis, it was found that there are three distinct regions. Damping force requirements for each region are different and critical. If wrong damping force is generated in any region, it may induce more acceleration/disturbance on vehicle, which is the main problem that existing methods suffer from. Proposed method generates right amount of force required at right time to suppress vibration by designing better control algorithm based on energy equations and dynamic equations. The proposed methods are validated by using simulations and experiments. For experimental validation of suspension system and attaining higher performance, accuracy of measurement system and parameters involved cannot be overlooked. Therefore, detailed investigations on accurate measurement system and parameter estimation methodology for suspension system were conducted. Thorough analysis on existing measurement system revealed critical errors in existing measurement system. To find out root cause of problems an analytical formula for evaluation of measurement system was derived. To overcome measurements issues it is required to use time, instead of encoders, as scalar base. This is not possible in existing methods, as sampling time of existing methods is dependent on other associated systems. Therefore, new measurement system is proposed, which uses high frequency clock and high sampling frequency to measure accurate time as soon as change in displacement occurs. This is same as using a stopwatch with a resolution as low as Nanoseconds. Simulations and experiments proved the proposed strategy and its effectiveness. The achieved accuracy from proposed method is comparable to the speed measurements system based on laser interferometer system. After having accurate measurement system for suspension system, accuracy of systems’ parameters is evaluated from accuracy point of view. The estimation problem is a mathematical problem in which number of independent equations are less than parameters to be estimated, which makes this problem unsolvable. Existing approaches use excitation method to generate additional equations and convert system to an overdetermined system and hence to be solved and an optimization problem. Getting overdetermined system is not a solution to the problem as independent equations are still the same. Furthermore, existing methods do not take care of coupling effects, eliminating or isolating noise and parameters from each other. Therefore, parameters estimation is not accurate. This motivated to develop an algorithm to estimate parameters with more accuracy and reliability. The proposed method converts estimation problem into a control problem and the parameters are updated by generating step-by-step update based on state feedback and projecting input on error of states or their functions. Properly designed desired trajectories for different parameters are used to decouple the parameter from other parameters. A systematic way of updating one parameter at a time in different cycles ensured convergence of parameters to true value even if absolute decoupling between parameters is not possible for complicate and nonlinear systems. The proposed method is validated, for linear and nonlinear problems by simulations and experiments.

This paper considers experiments on the control of a helicopter gearbox hybrid electromagnetic suspension. As the new generation of helicopters includes variable engine revolutions per minute (RPMs) during flight, it becomes relevant to add active control to their suspension systems. Most active system performance derives directly from the controller construction, its optimization to the system controlled, and the disturbances expected. An investigation on a feedback and feedforward filtered-x least mean square (FXLMS) control applied to an active DAVI suspension has been made to optimize it in terms of narrow-band disturbance rejection. In this paper, we demonstrate the efficiency of a new hybrid active suspension by combining the advantages of two different approaches in vibration control: resonant absorbers and active suspensions. Here, a hybrid active suspension based on the passive vibration filter called DAVI is developed. The objective of this paper is to prove the relevancy of coupling a resonant vibration absorber with a control actuator in order to create an active suspension with larger bandwidth efficiency and low energy consumption. The simulations and experimentation achieved during this suspension system development support this hypothesis and illustrate the efficiency and low energy cost of this smart combination.

When a tyre blows out, the vehicle’s trajectory deviates from the intended path, resulting in an accident and death. Because of its larger contact patch, applying more steering force to the flat tyre will cause the tyre to separate from the wheel. Also, improper braking effort causes rollover related issues due to the sudden vehicle’s centre of gravity (C.G.) displacement and weight transfer towards the blow-out tyre. Therefore, this research attempts to return the C.G. to its initial position through the suspension control. The force supplied between the sprung and unsprung masses of the flat tyre through suspension actuator is estimated and controlled by the model predictive control (MPC) scheme with respect to its input signals. For the non-linear simulation, the four-wheel passenger car vehicle dynamic model and the combined empirical model for the tyre inflation pressure effect are used. And the equivalent plant model is identified through a simple system identification method for the MPC design. The passive and active based suspension of standalone, roll-resistant interconnected and pitch-resistant interconnected systems, including the proposed comfort-lateral trajectory controlled standalone active suspension, were examined. To assess the effectiveness of each suspension and its control strategy in a tyre blow-out scenario, a vehicle was analysed with various longitudinal velocities along with and without steer input.

This paper presents a novel control strategy employing the artificial neural network-based direct torque control (DTC) strategy and direct power control (DPC) strategy for permanent magnet synchronous generator (PMSG)-based wind energy conversion system (WECS). The Aeolos 3 kW wind system ratings are considered in this paper for real time system validation. The proposed control strategy combines artificial neural network (ANN)-based DTC as machine side control (MSC) strategy and ANN-based DPC as grid side control (GSC) strategy in order to track the maximum power and to regulate the active power, respectively. To generate the switching pulse for the converter in generator side and grid side, a neural network-based technique is employed. Furthermore, the DC link voltage is optimised using the GSC topology. The proposed controller provides a stable voltage and power which is an effective solution for grid integration and constant power flow from the generator system to the grid system. The proposed coordinate control strategy is validated using MATLAB/Simulink software to analysis the working condition. The experimental test bench is implemented using dSPACE to study the real time analysis of the proposed control strategy.

Human drivers have rich and diverse driving characteristics on curved roads. Finding the characteristic quantities of the experienced drivers during curve driving and applying them to the steering control of autonomous vehicles is the research goal of this article. We first recruited 10 taxi drivers, 5 bus drivers, and 5 driving instructors as the representatives of experienced drivers and conducted a real car field experiment on six curves with different lengths and curvatures. After processing the collected driving data in the Frenet frame and considering the free play of a real car’s steering system, it was interesting to observe that the shape enclosed by steering wheel angles and the coordinate axis was a trapezoid. Then, we defined four feature points, four feature distances, and one feature steering wheel angle, and the trapezoidal steering wheel angle (TSWA) model was developed by backpropagation neural network with the inputs were vehicle speeds at four feature points, and road curvature and the outputs were feature distances and feature steering wheel angle. The comparisons between TSWA model and experienced drivers, model predictive control, and preview-based driver model showed that the proposed TSWA model can best reflect the steering features of experienced drivers. What is more, the concise expression and human-like characteristic of TSWA model make it easy to realize human-like steering control for autonomous vehicles. Lastly, an autonomous vehicle composed of a nonlinear vehicle model and electric power steering (EPS) system was established in Simulink, the steering wheel angles generated by TSWA model were tracked by EPS motor directly, and the results showed that the EPS system can track the steering angles with high accuracy at different vehicle speeds.

<div class="section abstract"><div class="htmlview paragraph">The performance of suspension system has a direct impact on the riding comfort and smoothness. For the traditional suspension can not effectively alleviate the impact of road surface and the poor anti-vibration performance, The dynamics model of vehicle suspension system is established, and the control model of vehicle four-degree-of-freedom active suspension is designed with fuzzy control strategy. On this basis, a comprehensive simulation model of the control model of vehicle active suspension coupled with road excitation is established. and the ride comfort of vehicles under different types of suspension are tested through Simulink. The simulation results show that compared with the passive suspension, the reduction of vehicle acceleration and dynamic deformation of the active suspension controlled by fuzzy PID can reach 33.76% and 22.45%. and the reduction of pitch Angle speed and dynamic load of the active suspension controlled by fuzzy PID can reach 16.18% and 10.72%. Under fuzzy PID control, the amplitude of each evaluation index of active suspension in the suspension system is substantially reduced than that of the passive suspension, and the root-mean-square value decreases by about 10% on average. It can be seen that the active suspension with fuzzy PID control can improve the performance of the suspension system on the basis of ensuring the stability and rapid response of the system, and can well reduce the random vibration caused by the impact of the vehicle on the random road surface during the driving process, improve the ride comfort, smoothness and ride safety of the vehicle, and achieve a good control effect on the vehicle suspension.</div></div>