Parametric Study of Factors Affecting Lateral Stability of a Public Transportation Vehicle

The availability of public transport is one of the solutions to traffic congestion in Jakarta. Focusing on angkot, one of the public transport types in Jakarta, this study discusses a model and simulations to investigate several factors that affect its lateral stability. Those factors include rear tire inflation pressure, passenger configuration, velocity, and downhill inclination angle. The results show that the stability of an angkot is proportional to the rear tires cornering stiffness. It also has an indirect relationship with the passenger configuration within the angkot. Moreover, the stability of an angkot decreases as its velocity and the angle of the inclined road increase. In general, this study is expected to have a contribution to the development of public transport in Jakarta, especially angkot.

Adaptive Kalman Filter with L2 Feedback Control for Active Suspension Using a Novel 9-DOF Semi-Vehicle Model

In order to further improve driving comfort, this paper takes the semi-vehicle active suspension as the research object. Furthermore, combined with a 5-DOF driver-seat model, a new 9-DOF driver seat-active suspension model is proposed. The adaptive Kalman filter combined with L2 feedback control algorithm is used to improve the controller. First, a discrete 9-DOF driver seat-active suspension model is established. Then, the L2 feedback algorithm is used to solve the optimal feedback matrix of the model, and the adaptive Kalman filter algorithm is used to replace the linear Kalman filter. Finally, the improved active suspension model and algorithm are verified through simulation and test. The results show that the new algorithm and model not only significantly improve the driver comfort, but also comprehensively optimize the other performance of the vehicle. Compared with the traditional LQG control algorithm, the RMS value of the acceleration experienced by the driver’s limb are, respectively, decreased by 10.9%, 15.9%, 6.4%, and 7.5%. The RMS value of pitch angle acceleration experienced by the driver decreased by 6.4%, and the RMS value of the dynamic tire deflection of front and rear tire decreased by 32.6% and 12.1%, respectively.

Influence of Tire Inflation Pressure on Vehicle Dynamics and Handling Performance

Tire inflation pressure affects both tire longitudinal and lateral stiffness and thus may impose a considerable influence on vehicle dynamics and handling performance. This paper presents a comprehensive study revealing the effects of tire pressure variations and their distribution among four tires on vehicle dynamics and handling performance. An extended Magic Formula tire model and a modified UniTire model involving tire inflation pressure are employed to describe the tire longitudinal and lateral forces, respectively. Two groups of vehicle maneuvers are simulated in CarSim: a single lane change maneuver with braking and a double lane change maneuver, to exhibit the effects of tire inflation pressure. Various tire pressure variations including all four tires at same and different pressures are examined. A vehicle dynamics, lateral motion stability index, and driver steering workload are utilized to quantify the influence of tire pressure variations and distributions. Analyses on the simulation results indicate that: 1) a front tire pressure reduction induces vehicle understeering tendency and a larger steering angle; 2) a rear tire pressure reduction causes oversteering characteristics and a sacrifice on vehicle stability with a larger vehicle sideslip angle; 3) all-tire inflation pressure decrease will increase driver’s steering workload; and 4) lower rear-tire inflation pressure can promote the combined performance of vehicle path-tracking and driver’s steering workload.

Multibody Simulation of an Electric Go-Kart: Influence of Power-Train’s Weight Distribution on Dynamic Performance

A multibody model of an electric go-kart was developed in Msc-Adams Car software to simulate the vehicle’s dynamic performance. In contrast to an ICE kart, its electric counterpart bares an extra weight load accounted for the batteries and other powertrain components. The model is inspired on a prototype vehicle developed at Universidad de los Andes. The prototype was built on top of an ICE frame where a PMAC motor, controller, battery pack and the subsequent powertrain components were installed. A petrol-based Go-kart weight distribution was defined as baseline and several variants of the electric adaptation with different weight distributions were constructed. The main objective of the model is to evaluate different configurations and identify the ones that can give performance advantages. Step steer simulations ran at 40 km/h (64 mph) were analyzed to assess the dynamic performance of the vehicle for different configuration of the battery bank placement. For most iterations of powertrain location, considerable differences in dynamic response were obtained and the handling balance was identified as Understeer contrary to a priori thoughs. Understeer gradient, weight distribution for both axles, trajectory among other results of interest were observed in the simulations. The model allowed to showcase the effect of redistribution of weight on the dynamic behavior in this specific application. Among the main consequences lies the fact that battery distribution can affect the lifting of the internal rear tire and the detriment in turning effectiveness.

Sensitivity analysis of three-wheel vehicle’s suspension parameters influencing ride behavior

In this article coupled vertical–lateral 9 degree-of-freedom model of a three-wheel vehicle formulated using Lagrangian dynamics is presented in order to determine its vertical and lateral ride. The model is justified by correlating the power spectral density vertical and lateral acceleration results determined from analysis with the same obtained from experimental measurements. The ride comfort of the vehicle is evaluated on the basis of ISO 2631-1 criteria. The sensitivity of vehicle suspension parameters on vertical and lateral ride behavior is analyzed, and it is noticed that rear-suspension damping coefficient, front-tire stiffness, rear-tire stiffness, front-tire damping coefficient, and rear-tire damping coefficient are critical parameters for vertical power spectral density acceleration. Rear-suspension stiffness, rear-suspension damping coefficient, front-tire stiffness, and rear-tire stiffness are critical parameters for lateral power spectral density acceleration.

An Improved Multiobjective Particle Swarm Optimization Algorithm Using Minimum Distance of Point to Line

In a multiobjective particle swarm optimization algorithm, selection of the global best particle for each particle of the population from a set of Pareto optimal solutions has a significant impact on the convergence and diversity of solutions, especially when optimizing problems with a large number of objectives. In this paper, a new method is introduced for selecting the global best particle, which is minimum distance of point to line multiobjective particle swarm optimization (MDPL-MOPSO). Using the basic concept of minimum distance of point to line and objective, the global best particle among archive members can be selected. Different test functions were used to test and compare MDPL-MOPSO with CD-MOPSO. The result shows that the convergence and diversity of MDPL-MOPSO are relatively better than CD-MOPSO. Finally, the proposed multiobjective particle swarm optimization algorithm is used for the Pareto optimal design of a five-degree-of-freedom vehicle vibration model, which resulted in numerous effective trade-offs among conflicting objectives, including seat acceleration, front tire velocity, rear tire velocity, relative displacement between sprung mass and front tire, and relative displacement between sprung mass and rear tire. The superiority of this work is demonstrated by comparing the obtained results with the literature.

Dynamics of Tire Blowout Events and Driver Assist System for Controlling Them

Dynamics of a pickup truck undergoing a rear tire blowout are analyzed as a system controlled by a human driver. Analysis is based on a large nonlinear vehicle dynamics model combined with a human driver model. The main reason why some tire blowouts result in accidents is identified. Insight is generated in experiments with human drivers in a driving simulator that runs the same vehicle model as the one used for analysis. A driver assist system for controlling tire blowouts is developed and validated in real time in the driving simulator.

A Controller Framework for Autonomous Drifting: Design, Stability, and Experimental Validation

This paper presents the development of a controller for autonomous, steady-state cornering with rear tire saturation (“drifting”) of a rear wheel drive vehicle. The controller is designed using a three-state vehicle model intended to balance simplicity and sufficient model fidelity. The model has unstable “drift equilibria” with large rear drive forces that induce deep rear tire saturation. The rear tire saturation at drift equilibria reduces vehicle stability but enables “steering” of the rear tire force through friction circle coupling of rear tire forces. This unique stability–controllability tradeoff is reflected in the controller design, through novel usage of the rear drive force for lateral control. An analytical stability guarantee is provided for the controller through a physically insightful invariant set around a desired drift equilibrium when operating in closed-loop. When implemented on a by-wire testbed, the controller achieves robust drifts on a surface with highly varying friction, suggesting that steady cornering with rear tire saturation can prove quite effective for vehicle trajectory control under uncertain conditions.