Powertrain Control for Active Damping of Driveline Oscillations

When a vehicle is subjected to acceleration or disturbances, the elasticity of the various components in the driveline may cause torsional vibrations which can result in an oscillating vehicle speed. These driveline oscillations are also known as shuffle and are low frequency oscillations corresponding to the first resonance frequency of the driveline. The oscillations give rise to, apart from material stress, noticeable lessened driveability. In this work, different ways to actively damp the oscillations are investigated. The idea is to use the engine as an actuator in order to achieve active damping, so-called active engine control. Different linear controllers are investigated and evaluated. The paper includes driveline modelling, control design and verifications by simulations, and tests in real vehicle. Implementation issues such as limited amount of available engine torque and parameter identifications are also discussed. A Linear-Quadratic-Gaussion (LQG) controller has been implemented and tested on a heavy duty truck. Results show that the LQG controller works well and active damping is achieved.     

Powertrain Control for Active Damping of Driveline Oscillations

When a vehicle is subjected to acceleration or disturbances, the elasticity of the various components in the driveline may cause torsional vibrations which can result in an oscillating vehicle speed. These driveline oscillations are also known as shuffle and are low frequency oscillations corresponding to the first resonance frequency of the driveline. The oscillations give rise to, apart from material stress, noticeable lessened driveability. In this work, different ways to actively damp the oscillations are investigated. The idea is to use the engine as an actuator in order to achieve active damping, so-called active engine control. Different linear controllers are investigated and evaluated. The paper includes driveline modelling, control design and verifications by simulations, and tests in real vehicle. Implementation issues such as limited amount of available engine torque and parameter identifications are also discussed. A Linear-Quadratic-Gaussion (LQG) controller has been implemented and tested on a heavy duty truck. Results show that the LQG controller works well and active damping is achieved.     

A passenger car driver model for higher lateral accelerations

Due to increasing demands for time and cost efficient vehicle and driver assistant systems development, numerical simulation of closed-loop manoeuvres becomes increasingly important. Thus, the driver has to be considered in the modelling. On the basis of a two-layer approach to model a driver's steering behaviour, the field of application is extended to higher lateral accelerations in this study. An analytical method to determine the driver parameters is presented, which is based on the two-wheel vehicle model. The simulation results are determined using a full vehicle model including all essential nonlinearities. Standard manoeuvres in the nonlinear range of vehicle handling behaviour are performed. A cornering manoeuvre is chosen to show the characteristics of the proposed driver model.     

A passenger car driver model for higher lateral accelerations

Due to increasing demands for time and cost efficient vehicle and driver assistant systems development, numerical simulation of closed-loop manoeuvres becomes increasingly important. Thus, the driver has to be considered in the modelling. On the basis of a two-layer approach to model a driver's steering behaviour, the field of application is extended to higher lateral accelerations in this study. An analytical method to determine the driver parameters is presented, which is based on the two-wheel vehicle model. The simulation results are determined using a full vehicle model including all essential nonlinearities. Standard manoeuvres in the nonlinear range of vehicle handling behaviour are performed. A cornering manoeuvre is chosen to show the characteristics of the proposed driver model.     

Optimization of Vehicles Elasto-Damping Elements Characteristics from the Aspect of Ride Comfort

SUMMARY

Spatial random vibrations of a vehicle that arise during driving represent an important factor in functioning of a dynamic system: Driver - Vehicle - Environment. They carry certain information for driver and also cause fatigue of driver and passenger.

This is the reason why the tendency is towards the minimization of vibratory loads, what in practice can be achieved by optimization of characteristics of elasto - damping elements of a vehicle.

In this paper for optimization of elasto - damping elements of a vehicle we used a complex nonlinear model of a driver and a vehicle during the straight - line motion of the vehicle on a rough road. Optimization was performed by application of the Hooke - Jeeves method and by use of outside penalty functions as well as the objective function that enabled simultaneous optimization of vertical vibrations of the driver's seat, vibrations of the steering wheel, and normal reactions in the contact surface of the tyre and road. The optimization was performed with application of the computer HP 9000/800 SE on the example of a medium passenger car.     

The Horsepower Reserve Formulation of Driveability for a Vehicle Fitted With a Continuously Variable Transmission

Summary A systematic methodology is developed for choosing the optimum ratio trajectory of a continuously variable transmission in a passenger vehicle. The optimum CVT ratio schedule is formulated as a constrained optimization problem with maximum fuel economy as the objective function and driveability concerns and physical limitations included as the constraints. The key notion to achieving good driveability is the introduction and definition of a horsepower reserve function that creates a consistent and desirable vehicle response under different driving conditions. Simulation results compare the optimized schedule's performance with several other possible ratio schedules, including the minimum brake specific fuel consumption map. Results from the optimized schedule indicate only a mild tradeoff between driveability and fuel economy relative to the other ratio schedules. The ratio optimization problem formulation and solution provide a novel and unique approach for systematically addressing driveability and fuel economy considerations associated with a continuously variable transmission.     

Development of a Strategy Model of the Driver in Lane Keeping

Based on vehicle constraints and known human operator characteristics, a strategy model was postulated for describing behavior in the lane keeping task. This model includes nonlinear thresholds operating on vehicle yaw and lateral translation, random input sources to account for spurious driver activity, and smoothing to account for driver response lag. The output of the model is steering wheel position

To determine model parameters and model suitability in describing driver behavior, recordings were made for driver-subjects performing a lane-keeping task in a moving base driving simulator having a computer generated display. A procedure involving both analytic and experimental techniques was then developed for determining the model parameters of each driver

Statistical comparisons and visual inspections made between driver-vehicle and model-vehicle time histories indicate a high degree of correspondence. Models such as these show promise in obtaining a better understanding of driver behavior and driver-vehicle response by incorporating nonlinear elements in the driver model.     

Analysis of a special purpose vehicle’s behaviour after an edge drop-off onto a soft shoulder

The article concerns the dynamics of a four-axle 20 ton special purpose vehicle in the driver’s panicky defensive manoeuvre resulting from edge drop-off of wheels onto a soft shoulder. A calculation model in the PC-Crash software environment has been developed to include the complex mechanism of the soft soil response to the wheel movement. The analysis of the results indicates the danger manifested by strong wheels vibrations, instantaneous change of vehicle steerability characteristics and a high rate of increase of the yaw angle and vehicle pitch during braking with steered wheels turned. The calculations indicate an extremely adverse effect of the phase of vehicle oversteer which in the analysed motion of the vehicle lasts over 1.5 s. The calculations prove that in such a short time the driver has very little chance of any practical response to the non-typical behaviour of the vehicle which otherwise is, in general, understeered.     

Finite Disturbance Directional Stability of Vehicles with Human Pilot Considering Nonlinear Cornering Behavior

The driver of a vehicle has a significant influence on handling and stability of the vehicle. Due to the complex behavior of a human pilot, a driver model is usually neglected when dealing with the problem of vehicle stability. This work focuses on the interaction between the vehicle and the human pilot. A model characterizing human operator behavior in a regulation task is employed to study directional stability. Linear stability is analyzed by the application of the Routh-Hurwitz criterion and stability boundaries separating the stable domain of operation of the driver from the unstable one are constructed.

The linear analysis predicts that the only possible instability in a driver/vehicle system is an oscillatory instability with increasing amplitude. It is shown that the addition of kinematic as well as slip angle nonlinearities in the vehicle model can have a stabilizing effect on these oscillations of the combined driver/vehicle system. They may also be responsible for the opposite, namely a linearly stable motion may become unstable to finite size disturbances. These nonlinear motions are predicted by a bifurcation analysis and are verified by direct numerical simulation.     

In-depth understanding of lane changing interactions for in-vehicle driving assistance systems

Lane-changing events are often related with safety concern and traffic operational efficiency due to complex interactions with neighboring vehicles. In particular, lane changes in stop-and-go traffic conditions are of keen interest because these events lead to higher risk of crash occurrence caused by more frequent and abrupt vehicle acceleration and deceleration. From these perspectives, in-depth understanding of lane changes would be of keen interest in developing in-vehicle driving assistance systems. The purpose of this study is to analyze vehicle interactions using vehicle trajectories and to identify factors affecting lane changes with stop-and-go traffic conditions. This study used vehicle trajectory data obtained from a segment of the US-101 freeway in Southern California, as a part of the Next Generation Simulation (NGSIM) project. Vehicle trajectories were divided into two groups; with stop-and-go and without stop-and-go traffic conditions. Binary logistic regression (BLR), a well-known technique for dealing with the binary choice condition, was adopted to establish lane-changing decision models. Regarding lane changes without stop-and-go traffic conditions, it was identified based on the odd ratio investigation that he subject vehicle driver is more likely to pay attention to the movement of vehicles ahead, regardless of vehicle positions such as current and target lanes. On the other hand, the subject vehicle driver in stop-and-go traffic conditions is more likely to be affected by vehicles traveling on the target lane when deciding lane changes. The two BLR models are adequate for lane-changing decisions in normal and stop-and-go traffic conditions with about 80 % accuracy. A possible reason for this finding is that the subject vehicle driver has a tendency to pay greater attention to avoiding sideswipe or rear-end collision with vehicles on the target lane. These findings are expected to be used for better understanding of driver’s lane changing behavior associated with congested stop-and-go traffic conditions, and give valuable insights in developing algorithms to process sensor data in designing safer lateral maneuvering assistance systems, which include, for example, blind spot detection systems (BSDS) and lane keeping assistance systems (LKAS).     

Nonlinear PI front and rear steering control in four wheel steering vehicles

Vehicle steering dynamics show resonances, which depend on the longitudinal speed, unstable equilibrium points and limited stability regions depending on the constant steering wheel angle, longitudinal speed and car parameters.

The main contribution of this paper is to show that a combined decentralized proportional active front steering control and proportional-integral active rear steering control from the yaw rate tracking error can assign the eigenvalues of the linearised single track steering dynamics, without lateral speed measurements, using a standard single track car model with nonlinear tire characteristics and a non-linear first-order reference model for the yaw rate dynamics driven by the driver steering wheel input. By choosing a suitable nonlinear reference model it is shown that the responses to driver step inputs tend to zero (or reduced) lateral speed for any value of longitudinal speed: in this case the resulting controlled vehicle static gain from driver input to yaw rate differs from the uncontrolled one at higher speed. The closed loop system shows the advantages of both active front and rear steering control: higher controllability, enlarged bandwidth for the yaw rate dynamics, suppressed resonances, new stable cornering manoeuvres, enlarged stability regions, reduced lateral speed and improved manoeuvrability; in addition comfort is improved since the phase lag between lateral acceleration and yaw rate is reduced.

For the designed control law a robustness analysis is presented with respect to system failures, driver step inputs and critical car parameters such as mass, moment of inertia and front and rear cornering stiffness coefficients. Several simulations are carried out on a higher order experimentally validated nonlinear dynamical model to confirm the analysis and to explore the robustness with respect to unmodelled dynamics.     

Nonlinear PI front and rear steering control in four wheel steering vehicles

Vehicle steering dynamics show resonances, which depend on the longitudinal speed, unstable equilibrium points and limited stability regions depending on the constant steering wheel angle, longitudinal speed and car parameters.

The main contribution of this paper is to show that a combined decentralized proportional active front steering control and proportional-integral active rear steering control from the yaw rate tracking error can assign the eigenvalues of the linearised single track steering dynamics, without lateral speed measurements, using a standard single track car model with nonlinear tire characteristics and a non-linear first-order reference model for the yaw rate dynamics driven by the driver steering wheel input. By choosing a suitable nonlinear reference model it is shown that the responses to driver step inputs tend to zero (or reduced) lateral speed for any value of longitudinal speed: in this case the resulting controlled vehicle static gain from driver input to yaw rate differs from the uncontrolled one at higher speed. The closed loop system shows the advantages of both active front and rear steering control: higher controllability, enlarged bandwidth for the yaw rate dynamics, suppressed resonances, new stable cornering manoeuvres, enlarged stability regions, reduced lateral speed and improved manoeuvrability; in addition comfort is improved since the phase lag between lateral acceleration and yaw rate is reduced.

For the designed control law a robustness analysis is presented with respect to system failures, driver step inputs and critical car parameters such as mass, moment of inertia and front and rear cornering stiffness coefficients. Several simulations are carried out on a higher order experimentally validated nonlinear dynamical model to confirm the analysis and to explore the robustness with respect to unmodelled dynamics.     

Study on driver model for hybrid truck based on driving simulator experimental results

In this paper, a proposed car-following driver model taking into account some features of both the compensatory and anticipatory model representing the human pedal operation has been verified by driving simulator experiments with several real drivers. The comparison between computer simulations performed by determined model parameters with the experimental results confirm the correctness of this mathematical driver model and identified model parameters. Then the driver model is joined to a hybrid vehicle dynamics model and the moderate car following maneuver simulations with various driver parameters are conducted to investigate influences of driver parameters on vehicle dynamics response and fuel economy. Finally, major driver parameters involved in the longitudinal control of drivers are clarified.     

Steering disturbance rejection using a physics-based neuromusculoskeletal driver model

The aim of this work is to develop a comprehensive yet practical driver model to be used in studying driver–vehicle interactions. Drivers interact with their vehicle and the road through the steering wheel. This interaction forms a closed-loop coupled human–machine system, which influences the driver's steering feel and control performance. A hierarchical approach is proposed here to capture the complexity of the driver's neuromuscular dynamics and the central nervous system in the coordination of the driver's upper extremity activities, especially in the presence of external disturbance. The proposed motor control framework has three layers: the first (or the path planning) plans a desired vehicle trajectory and the required steering angles to perform the desired trajectory; the second (or the musculoskeletal controller) actuates the musculoskeletal arm to rotate the steering wheel accordingly; and the final layer ensures the precision control and disturbance rejection of the motor control units. The physics-based driver model presented here can also provide insights into vehicle control in relaxed and tensed driving conditions, which are simulated by adjusting the driver model parameters such as cognition delay and muscle co-contraction dynamics.     

Simulation of Vehicle and Power Steering Dynamics Using Tire Model Parameters Matched to Whole Vehicle Experimental Results

This paper uses simulation to investigate how vehicle loading conditions (driver only, passengers, cargo, and fuel) affect power steering system and overall vehicle dynamics. Our purpose of the study was to evaluate the power steering system model for possible use in the National Advanced Driving Simulator (NADS). The effects of changing loading conditions on inertial properties of passenger cars have been found experimentally using a Vehicle Inertia Measurement Facility (VIMF). This paper presents simulation results using a vehicle handling model combined with a power steering system model and a nonlinear tire model. A crucial part of this project was the adjustment of certain parameters of Pacejka's tire model in order to match simulation results with experimental measurements of vehicle and power steering variables in transient maneuvers.     

Simulation of Vehicle and Power Steering Dynamics Using Tire Model Parameters Matched to Whole Vehicle Experimental Results

This paper uses simulation to investigate how vehicle loading conditions (driver only, passengers, cargo, and fuel) affect power steering system and overall vehicle dynamics. Our purpose of the study was to evaluate the power steering system model for possible use in the National Advanced Driving Simulator (NADS). The effects of changing loading conditions on inertial properties of passenger cars have been found experimentally using a Vehicle Inertia Measurement Facility (VIMF). This paper presents simulation results using a vehicle handling model combined with a power steering system model and a nonlinear tire model. A crucial part of this project was the adjustment of certain parameters of Pacejka's tire model in order to match simulation results with experimental measurements of vehicle and power steering variables in transient maneuvers.     

换道操作对智能车辆乘客舒适性的影响研究

乘坐舒适性是决定乘客对智能车辆接受度的重要因素之一。为了提升智能车辆的舒适性,服务智能驾驶控制算法的设计和优化,开展了基于乘客主观感知的实车乘坐舒适性试验,试验中驾驶人驾驶传统车辆执行多次换道操作,获取了60名被试乘客对换道操作的舒适性评价数据,并采集了车辆的运动数据。选取换道时横向最大加速度、回正时横向最大加速度、横向最大加加速度、横向加速度转换幅值以及横向加速度转换频率这5个车辆运动参数作为研究对象。采用二元Logistic回归单因素分析法分析了这5个车辆运动参数对乘坐舒适性的影响,采用接收者操作特征(ROC)曲线分析法为不同晕车易感性的乘客分别确立了这5个车辆运动参数的舒适性阈值,并根据岭回归分析法确定了不同参数对乘坐舒适性的影响权重。结果表明：所选取的5个车辆运动参数对乘坐舒适性具有显著影响,易晕乘客的舒适性阈值小于不易晕乘客的舒适性阈值,在换道过程中,换道时横向最大加速度、回正时横向最大加速度和横向加速度转换幅值是影响乘坐舒适性的主要因素。最后根据车辆运动参数和乘客生理特征参数建立了基于动态时间归整(DTW)和K最近邻(KNN)算法的乘坐舒适性预测模型,该模型对乘坐舒适性的预测准确率为84%,可用于智能车辆控制算法的舒适性判断。     

Two degrees of freedom PID multi-controllers to design a mathematical driver model: experimental validation and robustness tests

This paper proposes a mathematical driver model based on PID multi-controllers having two degrees of freedom. Each PID controller making up this model is synthesised by the Ziegler–Nichols oscillation method, using the linear time invariant models which are obtained around their nominal operating points. Different PID controllers are combined using nonlinear optimisation and the H _∞ constraint. To demonstrate its robustness, it was tested on two models: a linear parameter variant model and a nonlinear four-wheel model. It was also tested in situations of high dynamic demand. The driver model showed good performance, stability and trajectory tracking. The performance tests were carried out using experimental data acquired by a Laboratory Peugeot 307 developed by INRETS-MA. This driver model was developed for an application known as ‘Itinerary Rupture DIagnosis’ (DIARI), which aims to evaluate the physical limits of a vehicle negotiating a bend. DIARI requires a tool to determine the steering commands to be applied to a vehicle model, making extrapolations with respect to speed.     

Evaluation of preview G-Vectoring control to decelerate a vehicle prior to entry into a curve

This paper describes the development of the braking assistance system based on a “G-Vectoring” concept. The present work focuses in particular on “Preview G-Vectoring Control” (PGVC), which is based on the “G-Vectoring Control” (GVC) scheme. In GVC, the longitudinal-acceleration control algorithm is based on the actual lateral jerk. PGVC decelerates a vehicle before it enters a curve, and is based on a new longitudinal-acceleration control algorithm which uses predicted and actual lateral jerk. Using the predicted lateral jerk makes it possible to decelerate the vehicle prior to curve entry. This deceleration can emulate a driver’s deceleration as the vehicle approaches a curve entry. PGVC is based on such deceleration algorithms and enables automatic deceleration similar to the action of a driver. It is thus possible to significantly improve the driver’s feeling when this system is activated. Driving tests with this new control system on snowy-winding course confirmed that the automatic brake control quality improved considerably compared to manual driver control considering both lap time and ride quality. These results indicate that PGVC can be a useful braking assistance system not only to improve the driver’s handling performance but also to reduce the brake-task during driving on winding roads.     

On Inverse Equations for Vehicle Dynamics

Instead of writing equations which when solved yield the response of a vehicle to an input such as the front wheel steer angle, one can often invert the equations so that a response quantity is specified as an input and a new set of equations is solved yielding the steer angle required as an output. Using these equations one can discover the input steer angle a driver would need to impose in order to accomplish a specific maneuver for various vehicles.

It is shown that there are many possible inverse equation sets and that the eigenvalues of the inverse equations are hard to interpret since they may have little to do with the vehicle parameters. The linear single-input single-output case is studied first to fix ideas using a simple example. For the bicycle model vehicle, it is shown that any vehicle may have unstable inverse equations depending upon the response quantity used. Extensions to nonlinear and multiple-input multiple output systems are discussed.