Virtual Chassis Research Articles

Ride comfort assessment for automated vehicles utilizing a road surface model and Monte Carlo simulations

AbstractThe growing number of automated vehicles (AVs) necessitates good ride comfort for passengers. This research investigates currently available ride comfort methods and evaluates their performance with a validated simulation framework. The methodology developed encompasses a high‐precision road surface model and uses Monte Carlo simulations to compile accurate and representative virtual chassis acceleration data. By utilizing a threshold method and standard ISO 2631 ride comfort guidelines, results are compared to classifications based on empirical International Roughness Index data. A case study conducted in Austria specifies that ISO 2631 comfort estimates are most similar to International Roughness Index classifications and that the thresholding procedure detects preventable situations and over‐ or underestimated ride comfort. Thus, this methodology can help to better understand requirements for AVs' comfort, as well as justifying the importance of developing a sophisticated performance metric.

Visualisation of the Motion Trajectory for Rolling Motion of Snake Robots using Virtual Chassis and Simplified Kinematics Motion Model

Abstract: The ability to visualise the motion trajectory of snake robots is important for path-planning and control and thus, their effectiveness in operation. This paper focuses on visualising the motion trajectory of snake robots in a rolling gait. Rolling is a relatively simple gait, but not all snake robots roll in a straight line, tending to deviate in the direction towards the centre of mass of snake robots. A kinematics motion model is used to capture the differential motion of each module of the snake robot between time-steps with the assumption that the underside of each module interacts with flat ground as a wheel. The virtual chassis approach then allows us to separate the internal body shape of the snake robot from the world frame and simplify modelling of the overall motion. Results obtained from modelling and experimentation are presented in this paper to validate the accuracy of the predicted motion trajectory.

수학적 모터 모델 기반 연료전지 자동차 가상 플랫폼 개발

A virtual chassis platform for Fuel Cell Hybrid Electric Vehicles(FCHEV) has been developed, and a virtual platform similar to the actual system has been composed. In addition, major components such as a motor, fuel cell and battery for the virtual platform have been constructed by using a mathematical formulation. The FCHEV virtual platform using a detailed model based on the mathematical formula is capable of simulating various conditions according to changes of the control logic and component modules to evaluate performance, considering the vehicle dynamic characteristics. Usability of the mathematical model has been verified by comparative simulations according to the motor current control variation. In addition, reliability of the developed virtual chassis platform has been verified by simulating its fuel consumption with the UDDS(Urban Dynamometer Driving Schedule) FTP-72 velocity profile.

Virtual Chassis for Snake Robots: Definition and Applications

Intuitively representing the motion of a snake robot is difficult. This is in part because the internal shape changes that the robot uses to locomote involve the entire body and no single point on the robot intuitively represents the robot’s pose at all times. To address this issue, we present a method of defining body coordinate frames that departs from the typical convention of rigidly fixing a frame to a link on the robot, and instead define a body frame that is based on the averaged position of all of the robot’s links. This averaged frame serves as a virtual chassis that effectively isolates the internal motion of the robot’s shape changes from the external motion, due to the robot’s interaction with its surroundings. This separation of motion allows much simpler models—such as those derived for wheeled vehicles—to accurately approximate the motion of the robot as it moves through the world. We demonstrate the practical advantages of using the virtual chassis body frame by estimating the pitch and roll of a snake robot undergoing dynamic motion by fusing readings from its internal encoders, gyros, and accelerometers with an extended Kalman filter.