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A high-precision vehicle handling dynamic model is of great importance in both the analysis of system performance and development of stability controller. This study introduces a new modeling algorithm based on subspace identification. Different from traditional batchwise subspace identification method, the new modeling method is proposed in the framework of online realization and unbiased estimation, which is ensured by a recursive propagator method (PM) combined with a vector autoregressive with exogenous (VARX) input model. Also, an observable and controllable 4-order linear time-varying (LTV) vehicle handling dynamic model, including rolling motion, is presented. To validate the identification algorithm, real vehicle standard road tests, including the step input test and impulse input test, are conducted, and sampling data are collected to apply into the identification procedure. The feasibility and accuracy of this online identification method are demonstrated. Furthermore, the stability of identification method is validated by an identification process based on road test data with measurement noise interference, and the superiority of the proposed identifiable LTV model is proved compared to the linear time-invariant (LTI) model.

As the important performance of automobile, the vehicle handling stability has always been the focus of the research. The steering-by-wire (SBW) system is a major innovation to the traditional steering system, which brings new challenges to the research on the vehicle handling stability. In order to improve the vehicle handling stability and active safety of SBW, the multidomain model of SBW is established on the basis of proper simplification. A new vehicle handling stability evaluation method and its expression are proposed. The system parameters, vehicle handling and stability are studied by multidisciplinary design optimization (MDO), and selection of the system frequency response and time domain response characteristics have important influence on the key parameters analyzed in SBW system performance. The results show that the vehicle handling stability is significantly higher after the parameter optimization, which can be used to guide the parameters design and matching of the steering system.

The purpose of this study is to evaluate the handling stability of vehicle from the perspective of users using a multi-criteria decision-making approach with interval numbers. In order to achieve this purpose, the evaluation criteria easy for drivers to understand were constructed based on questionnaire, the interval weights of the criteria were calculated using the entropy weight method with interval numbers, and the interval TOPSIS method was used to evaluate the vehicle handling stability. As the improvement of the method, a new method to determine the crisp value of the interval weight was given, and the relative closeness index used for ranking alternatives was extended to a new additive ranking index. The proposed method was used to evaluate the handling stability of 12 vehicles, and the results may provide some basis for vehicle R & D and design.

In order to improve the stability of vehicle steering on low-adhesion road surfaces, this paper designed a hybrid robust control strategy, H2/H∞, for active front-wheel steering (AFS) based on robust control theory. Firstly, we analyzed the influence of the sidewall stiffness and road adhesion coefficient of the tires on vehicle stability, through which we can study the wheel deflection characteristics of low-adhesion roads. Secondly, the reference yaw velocity of the vehicle was calculated using the three-degrees-of-freedom model as the reference model, through which, taking the norm H∞ as the objective function and the norm H2 as the limit to control the output, the hybrid robust control strategy H2/H∞ of the AFS system on a low-adhesion road surface was developed. Finally, the simulation experiment was carried out by the Simulink/CarSim co-simulation platform and a hardware-in-the-loop (HIL) experiment. In this paper, the results show that the AFS control strategy can improve the vehicle handling stability on low-adhesion road surfaces, and the controller has good path tracking performance and robustness.

This paper proposes a novel adaptive hierarchical control approach for Steer-by-Wire (SbW) vehicles to improve the handling stability. The high-level stability control scheme contains a variable steering ratio (VSR) strategy based on the adaptive-network-based fuzzy inference system (ANFIS) and an active front steering (AFS) controller designed with the integral sliding mode method by tracking the expected yaw rate, in which the desired front wheel angle is generated to enhance the cornering stability performance. Besides, an adaptive tracking controller (ATC) for the SbW system is designed by using the adaptive sliding mode control method to achieve desired steering performance in the lower level. The proposed adaptive control strategy is validated with different driving circles from ISO standards in simulation tests and hardware-in-the-loop (HiL) experiments. The results demonstrate that the designed control approach improve the vehicle handling stability significantly, even in some extreme driving conditions.

Forecasting future driving conditions such as acceleration, velocity, and driver behaviors can greatly contribute to safety, mobility, and sustainability issues in the development of new energy vehicles (NEVs). In this brief, a review of existing velocity prediction techniques is studied from the perspective of traffic flow and vehicle lateral dynamics for the first time. A classification framework for velocity prediction in NEVs is presented where various state-of-the-art approaches are put forward. Firstly, we investigate road traffic flow models, under which a driving-scenario-based assessment is introduced. Secondly, vehicle speed prediction methods for NEVs are given where an extensive discussion on traffic flow model classification based on traffic big data and artificial intelligence is carried out. Thirdly, the influence of vehicle lateral dynamics and correlation control methods for vehicle speed prediction are reviewed. Suitable applications of each approach are presented according to their characteristics. Future trends and questions in the development of NEVs from different angles are discussed. Finally, different from existing review papers, we introduce application examples, demonstrating the potential applications of the highlighted concepts in next-generation intelligent transportation systems. To sum up, this review not only gives the first comprehensive analysis and review of road traffic network, vehicle handling stability, and velocity prediction strategies, but also indicates possible applications of each method to prospective designers, where researchers and scholars can better choose the right method on velocity prediction in the development of NEVs.

In order to study the influence of tire pressure change on the control of vehicle handling stability, the seven-degree-of-freedom theoretical model of automobile dynamics and tire theoretical model considering tire pressure were established. Considering the double lane conditions, the control stability of automobile is simulated, and the influence of tire pressure change on the control stability of automobile is analyzed. The simulation results show that when the tire pressure is too high or too small, the yaw rate of the vehicle in the process of high speed steering cannot be stable, which reduces the vehicle handling stability.

Non-linear system control has always been a difficult point for vehicle stabilization. To improve the vehicle handling performance, a comprehensive active-steering control method is proposed and derived. Different from traditional strategy, this new controller is based on a piecewise tyre modelling ideology combined with feedback linearization controlling method. In the linear region of wheel–terrain contact, vehicle dynamic system turns to be a linear system, an optimal control is designed for the sake of rapid response in tracking desired values. In the non-linear region, where the controlling difficulty always lies in, the tyre lateral force is described by a new polynomial formula model, which is simpler than magic formula model and more accurate than linear model. This new tyre modelling ideology ensures the feasibility of feedback linearization method in non-linear system control. To verify the proposed controller, a numerical seven-degrees-of-freedom vehicle model is built and validated by standard input simulation. Then, simulation under limit conditions, including high friction case and low friction case, are conducted and results are presented and discussed. Compared with optimal controller and free-control method, comprehensive controller has a much more desirable applicability in both cases and greatly improves the vehicle handling performance.

This research examines the emerging role of adaptive interval type-2 fuzzy logic systems (AIT2FLS) versus adaptive type-1 fuzzy logic system (AT1FLS) in vehicle handling by a new nonlinear model of the variable geometry suspension system (VGS) as a vehicle active suspension system. A proper controller is needed in order to have soft response and robustness against challenging vehicle maneuvers. Two controllers, including AT1FLS and AIT2FLS have been used in the paper. The proposed AIT2FLS can efficiently handle system uncertainties, especially in the presence of most difficult challenging vehicle maneuvers in comparison with AT1FLS. The interval type-2 fuzzy adaptation law adjusts the consequent parameters of the rules constructed on the Lyapunov synthesis approach. For this purpose, the kinematic equations are obtained for the vehicle double wishbone suspension system and they are substituted in a nonlinear vehicle handling model with eight degrees of freedoms (8DOFs). Thereby, a new nonlinear model for the analysis of VGS is obtained. The results indicate that between the two controllers, the proposed AIT2FLS has better overall vehicle handling, robustness and soft response.

In this paper, the effect of both passive and actively-modified vehicle handling characteristics on minimum time manoeuvring for vehicles with 4-wheel torque vectoring (TV) capability is studied. First, a baseline optimal torque vectoring strategy is sought, independent of any causal control law. An optimal control problem (OCP) is initially formulated considering 4 independent wheel torque inputs, together with the steering angle rate, as the control variables. Using this formulation, the performance benefit using torque vectoring against an electric drive train with a fixed torque distribution, is demonstrated. The sensitivity of TV-controlled manoeuvre time to the passive understeer gradient of the vehicle is then studied. A second formulation of the optimal control problem is introduced where a closed-loop torque vectoring controller is incorporated into the system dynamics of the OCP. This formulation allows the effect of actively modifying a vehicle’s handling characteristic via TV on its minimum time cornering performance of the vehicle to be assessed. In particular, the effect of the target understeer gradient as the key tuning parameter of the literature-standard steady-state linear single-track model yaw rate reference is analysed.

Rear axle compliance steering (RACS) is a technology of passive four-wheel steering, which is designed to improve the vehicle handling and stability at medium or high speed. This paper focuses on the dynamic behavior of the vehicle with RACS. Firstly, the compliance steering principle for different rear suspensions is illustrated. Then, the viscoelastic members with fractional order derivative properties are introduced into RACS, and the fractional order model of RACS is formulated. Next, the dynamic model of the vehicle with RACS is established, the adjusting rules for the compliance steering stiffness are derived, and the vehicle stability is investigated. Finally, numerical experiments are performed to illustrate the effects on the vehicle dynamic behavior caused by the compliance steering stiffness, the viscoelastic members and the vehicle longitudinal velocity. Research results show that, the vehicle with RACS has better dynamic characteristics than that without RACS at medium or high speed; and the compliance steering stiffness, the viscoelastic members and the vehicle longitudinal velocity have different impacts on the vehicle lateral dynamic behavior.

A path tracking controller based on active disturbance rejection control(ADRC) theory is presented in this paper to solve path tracking problem in inverse vehicle handling dynamics. The basic idea behind the work is to design an active disturbance rejection controller according to yaw rate and lateral displacement during a vehicle travels along a prescribed path to generate an expected trajectory which guarantees minimum clearance to the prescribed path. Aiming at this purpose, using preview follower theory, a linear extended state observer based on lateral displacement is designed. Considering yaw angle of vehicle, a non-linear combination function combined error of lateral displacement as well as error of yaw angle is designed according to monotone bounded hyperbolic of tangent function. Finally, a real vehicle test is executed to verify the rationality of the path tracking controller. At the same time, according to characteristics of pavement file in Carsim, a 3-D virtual pavement model is established and ride comfort simulation of random pavement is carried out in the software model. The results show that the minimum lateral position error of the generated path tracking trajectory can be good indicators of successful solving of the path tracking problem in inverse vehicle handling dynamics for ADRC. More precisely, there is higher calculation accuracy for the algorithm of the ADRC to solve the path tracking problem. The study can help drivers easily identify safe lane-keeping trajectories and area.

The number of studies that are supported suspension parameters with statistical methods is very small. However, many studies have been made on the dynamics of vehicle handling. For this reason, in this study, sensitivity analysis was performed using different stiffness values of the leaf spring and roll bar in the front suspension. The effects of the parameters on both static and dynamic analyzes were interpreted. In addition, the statistical t-test and Anova analysis were performed in order to compare means of two or three groups.

In this study, shape optimization was conducted for a vehicle’s rear suspension torsion beam to improve its dynamic handling performance. To determine the design variables affecting the vehicle roll characteristics, a sensitivity analysis was conducted using the result of a Taguchi experiment with 6 factors in 8 runs. The upper and lower-flange lengths and web thickness of the torsion beam section, as well as the vertical height difference between the inner and outer of torsion beams, were determined as design variables through sensitivity analysis of the opposite wheel travel test for optimization of the torsion beam axle. The Box–Behnken experimental design with 4 factors and 27 runs was performed using the selected design variables and by performing opposite wheel travel analysis according to the experimental design, and the response surface functions of the roll stiffness, roll steer coefficient, roll center height, and mass of the torsion beam were generated. Using these response functions, shape optimization was conducted for the torsion beam of the rear suspension system. Dynamic performance analysis was performed by applying the optimized H-shaped torsion beam to the rear suspension of the vehicle dynamics model, and it was validated that the dynamic response performance of the optimized vehicle was improved.

Four wheel steering (4WS) technology can effectively improve the vehicle handling stability and driving safety. In order to fully consider the influence of the rear wheel steering, the vehicle dynamics model of 4WS vehicle, including the rear wheel steering by wire and two degrees of freedom vehicle model of 4WS vehicle, is established in this paper. The desired yaw rate is obtained according to the variable transmission ratio strategy. The yaw rate tracking strategy is applied to 4WS vehicle and rear wheel steering resistance moment is taken into account. Based on the robust control theory, H2/H∞ mixed robust controller design is carried to research the stability control of 4WS vehicle. Finally, the closed-loop simulation added driver model based on preview theory is carried out. The simulation results indicate that the designed H2/H∞ mixed robust controller can achieve the stability control.

This paper proposes a constrained optimization-based torque control allocation method aimed to improve energy efficiency, and thus, driving range for electric vehicles. In the proposed method, the cost function is defined not only to achieve desired yaw moment for vehicle handling and stability, but also to minimize power losses for energy efficiency. The particular attention is paid to the power losses due to tire slips both longitudinally and laterally. The constraints are also set based on thorough investigation on various causes of power disppation such that the torque is allocated with restraint to use regenerative braking in its maximum capacity. The proposed control allocation method has been tested and verified to be effective on energy efficiency improvement through both simulation and experiment under various driving maneuvers.

The ultimate target for vehicle aerodynamicists is to develop vehicles that perform well on the road in real-world conditions. On the other hand, vehicle development today is performed mostly in controlled settings, using wind tunnels and computational fluid dynamics with artificially uniform freestream conditions and neglecting real-world effects due to road turbulence from the wind and other vehicles. Turbulence on the road creates a non-uniform and fluctuating flow field in which the length scales of the fluctuations fully encompass the length scales of the relevant aerodynamic flow structures around the vehicle. These fluctuations can be comparable in size and strength with the vehicle’s own wake oscillations. As a result, this flow environment can have a significant impact on the aerodynamic forces and on the sensitivity of these forces to various shape changes. Some aerodynamic devices and integral design features can perform quite differently from the way in which they do under uniform freestream conditions. In this paper, unsteady aerodynamics simulations are performed using the lattice Boltzmann method on a detailed representative automobile model with several design variants, in order to explore the effect of on-road turbulence on the aerodynamics and the various mechanisms that contribute to these effects.

This paper presents an advanced coordination of integrated control system which consist of three different controllers namely Electronic Stability Control (ESC), Active Front Steering (AFS), and Active Suspension (AS) using Fuzzy Logic Control (FLC) in order to improve vehicle handling, cornering stability, and rollover prevention with anti-lock brakingsystem (ABS) to avoid wheel locking during generating differential braking by ESC control. Based on a well-developed and validated fourteen degrees of freedom full vehicle model with non-linear tire characteristics, a reference yaw-roll plane vehicle model is introduced to compare and therefore control the yaw rate, side slip angle, and roll angle of the vehicle body. For rollover prevention indices, the dynamic load transfer ratio is defined to check the effectiveness of the proposed controller. The Coordination chassis control is based on the lateral acceleration value as input to FLC, and the outputs are the increment factors to the three controllers varying from zero to one. Three membership functions are chosen to represent the lateral acceleration as input to the supervisor controller, to define the control authority for each actuator. The universe of discourse for each membership function is selected according to the study of the effect of eachcontroller stand alone in vehicle performance. The numerical modelling is carried out through the MATLAB / Simulink environment which suits the control and optimization process. Different standard test maneuvers namely J-turn,fishhook, and double lane change have been carried out by considering standard test maneuvers with different driving speeds. The simulation results are compared during three cases namely, the uncontrolled system, the combined controller, and the proposed coordinated controller. The results show a substantial improvement of the vehicle stability in terms ofvehicle lateral acceleration, side slip angle, yaw rate, roll angle, and the for the developed coordinated controller compared to combined controller or the conventional system without control.

The integrated longitudinal and lateral dynamic motion control is important for four wheel independent drive (4WID) electric vehicles. Under critical driving conditions, direct yaw moment control (DYC) has been proved as effective for vehicle handling stability and maneuverability by implementing optimized torque distribution of each wheel, especially with independent wheel drive electric vehicles. The intended vehicle path upon driver steering input is heavily depending on the instantaneous vehicle speed, body side slip and yaw rate of a vehicle, which can directly affect the steering effort of driver. In this paper, we propose a dynamic curvature controller (DCC) by applying a newly-defined parameter, the dynamic curvature of the path, derived from vehicle dynamic state variables, yaw rate, side slip angle, and speed of a vehicle. The proposed controller, combined with DYC and wheel longitudinal slip control, is to utilize the dynamic curvature as a target control parameter for a feedback, avoiding estimating the vehicle side-slip angle. The effectiveness of the proposed controller, in view of stability and improved handling, has been validated with numerical simulations and a series of experiments during cornering engaging a disturbance torque driven by two rear independent in-wheel motors of a 4WD micro electric vehicle.

Objective testing of vehicle handling in winter conditions has not been implemented yet because of its low repeatability and its low signal-to-noise ratio. Enabling this testing, by identifying rob ...

In order to enhance the vehicle dynamics, this paper presents a novel and innovative yaw moment control system in which the longitudinal positions of the wheels are individually controlled. For this purpose, the proposed concept is analytically and numerically studied first, and it is shown that the method can considerably modify the inherent characteristics of a vehicle, such as the handling and the steerability. This system can generate a stabilizing yaw moment, without any considerable changes in the total lateral force and the total longitudinal force of the vehicle. Finally, a comprehensive vehicle model together with an intelligent fuzzy control strategy are developed to evaluate the effectiveness of the active variable-wheelbase system in different driving conditions. Based on the simulation results, this system has the potential to be considered as a new alternative technique for vehicle dynamics control in the future.

Real-time information about vehicle mass and road slope is important for vehicle handling and stability control. This paper proposes a two-layer based adaptive parameter estimator to estimate the vehicle mass and road slope under longitudinal moving condition. In the first layer of the estimator, the slowly changed vehicle parameter, such as vehicle mass or road slope on the smooth road, is estimated by a computationally efficient adaptive law. Then in the second layer of the estimator, an online adaptive observer is applied to obtain the real-time information of the road slope on the uneven road. The proposed estimator is first verified by the numerical simulations. A scaled remote control car is then built to conduct the experimental tests. By using the measured data from the scaled vehicle, the proposed parameter estimator is validated to be able to estimate the vehicle mass and road slope in the real experimental conditions. In order to clearly present the estimation performance and compare estimation results, the root mean square (RMS) values and the normalised root mean square (NRMS) values of the estimation errors are calculated. The experimental results indicate that the obtained average RMS values of vehicle mass estimation error and road slope estimation error are 0.44 and 4.06, respectively. Road slope estimation shows bigger estimation error due to the severer vibration caused by climbing up the steep road.

The steady-state powerslide of an automobile (large side slip angle, negative steering angle, large rear driving torque) is considered as a manoeuvre characterized by nonlinear tyre characteristics and saturated horizontal tyre forces. Due to its typically unstable nature, the powerslide motion has to be stabilized either by the driver or an active system by controlling the steering angle and/or the accelerator (and braking) pedal. Consequences, and an appropriate driver model have already been presented in literature. However, different powertrain configurations, such as rear-wheel drive (RWD), all-wheel drive (AWD), with open, locked and limited slip differentials have not yet been addressed in more detail. Also the effectiveness of redundant inputs, either from the driver or from a driver assist system, is discussed. An appropriate vehicle, powertrain and tyre model is introduced to analyse regular and powerslide steady-state cornering. Then a measure of joint controllability and observability of the modes of these steady-state, and locally linearized motions, is evaluated. It turned out that basically the powerslide motion can be more easily stabilized by controlling the longitudinal tyre forces in particular at vehicles with limited slip differential, for instance with respective throttle commands (by the driver) when utilising the yaw rate measurement only, but also steering angles of the front wheels may (additionally) be applied. In contrast, at regular cornering, the steering inputs are superior to throttle commands to control the lateral motion variables of the vehicle.

This paper presents an investigation into the road-holding ability of a vehicle equipped with a roll-plane hydraulically interconnected suspension system. Ideally, the roll-plane hydraulically interconnected suspension system has the capability to decouple the roll mode from all the other vehicle suspension modes. However, anti-roll bars are unable to decouple the warp mode from the other modes, and therefore they limit the travel of the wheels and weaken the road-holding ability of a vehicle on uneven road surfaces. In this paper, vehicle dynamic analysis is carried out with three different configurations: a vehicle with only a spring–damper as a benchmark vehicle; a vehicle with a spring–damper in conjunction with anti-roll bars; a vehicle with a spring–damper in conjunction with a roll-plane hydraulically interconnected suspension. Simulations and corresponding experimental verification with different road excitations are then implemented. The experimental results agree well with the simulations under low-frequency road excitations. The results demonstrate that, when the vehicle undergoes off-road driving, the anti-roll bars weaken the road-holding ability of the vehicle while the hydraulically interconnected suspension system has a negligible effect.