Search Results

Abstract Car manufacturers are continuously improving passenger comfort by advancing technologies including highly automated driving. Before the broad introduction of automated driving, specific human factors regarding passenger comfort must be considered, including motion sickness. Therefore, the identification of the frequency of motion sickness and associated factors in the population is needed to extrapolate the effects for future mobility systems. We conducted three surveys between 2015 and 2020, asking people questions about their experience with motion sickness in cars. Based on the responses of 1165 participants, gender and age showed a strong influence on the self-reported frequency of motion sickness. For deeper analysis, a logistic order regression model was used to estimate the frequency of motion sickness for different user typologies.

Abstract This article investigates the dynamics of non-smooth and nonlinear oscillations of a bicycle-car model, considering the tire-road separation. Road contact applies a non-holonomic constrain on the dynamics system that makes the equations of motion to be different under in-contact and off-contact conditions. The set of nonlinear equations of the system has been formulated based on nondimensionalization to minimize the number of parameters and generalize the results. To compare the quality of different suspensions in reducing the unpleasant no-contact conditions, we define a contact-free fraction indicator to measure the separation fraction time during a cycle of steady-state oscillation. An observation of frequency responses including vertical displacements, the pitch mode, and the domain of contact-free fraction of time has been investigated to clarify engineering design directions.

Abstract When the vehicle is under braking condition in the longitudinal motion, the vehicle body will tilt due to the inertial force in motion. A high amplitude will result in uncomfortable feelings of the occupant, such as nervousness or dizziness. To solve the problem, this article presents an adaptive damping system (ADS), which combines the vehicle anti-pitch compensation control with the mixed skyhook (SH) and acceleration-driven-damper (ADD) control algorithm. This ADS can not only improve the vibration effect of the vertical motion for the vehicle but also consider the longitudinal motion of the vehicle body. In addition, a new damper mechanical hardware-in-the-loop test bench is built to verify the effectiveness of the algorithm.

Abstract The ground-effect problems of loss of thrust and fountain-effect instabilities are quantified. Experiments to control and augment ground-effect lift and stability are presented, including jet momentum reflection and fountain redirection using various types of internal and external underbody ventral strakes. By strategically designing the vertical takeoff and landing (VTOL) ventral surface, reflection of the impinging fountain momentum is possible so that instead of losing 10% thrust while in ground-effect, remarkably, thrust is augmented 10% or more to a considerable height above the ground, in addition to stabilizing random pitch and roll moments caused by fountain instability.

Abstract A critical component of vehicle dynamic control systems is the accurate and real-time knowledge of the vehicle’s key states and parameters when running on the road. Such knowledge is also essential for vehicle closed-loop feedback control. Vehicle state and parameter estimation has gradually become an important way to soft-sense some variables that are difficult to measure directly using general sensors. In this work, a seven degrees-of-freedom (7-DOF) nonlinear vehicle dynamics model is established, where consideration of the Magic formula tire model allows us to estimate several vehicle key states using a hybrid algorithm containing an unscented Kalman filter (UKF) and a genetic algorithm (GA). An estimator based on the hybrid algorithm is compared with an estimator based on just a UKF. The results show that the proposed estimator has higher accuracy and fewer computation requirements than the UKF estimator.

Abstract In this article, a hierarchical coordinated control algorithm for integrating active rear steering and driving/braking force distribution (ARS+D/BFD) was presented. The upper-level control was synthesized to generate the required rear steering angle and external yaw moment by using a sliding-mode controller. In the lower-level controller, a control allocation algorithm considering driving/braking actuators and tire forces constraints was designed to assign the desired yaw moment to the four wheels. To this end, an optimization problem including several equality and inequality constraints were defined and solved analytically. Finally, computer simulation results suggest that the proposed hierarchical control scheme was able to help to achieve substantial enhancements in handling performance and stability.

Abstract Advanced passenger vehicles are complex dynamic systems that are equipped with several actuators, possibly including differential braking, active steering, and semi-active or active suspensions. The simultaneous use of several actuators for integrated vehicle motion control has been a topic of great interest in literature. To facilitate this, a technique known as control allocation (CA) has been employed. CA is a technique that enables the coordination of various actuators of a system. One of the main challenges in the study of CA has been the representation of actuator dynamics in the optimal CA problem (OCAP). Using model predictive control allocation (MPCA), this problem has been addressed. Furthermore, the actual dynamics of actuators may vary over the lifespan of the system due to factors such as wear, lack of maintenance, etc. Therefore, it is further required to compensate for any mismatches between the actual actuator parameters and those used in the OCAP.

Abstract This article presents a workflow for aerodynamic optimization of vehicles that for the first time combines the adjoint method and the efficient global optimization (EGO) algorithm in order to take advantage of both the gradient-based and gradient-free methods for aerodynamic optimization problems. In the workflow, the adjoint method is first applied to locate the sensitive surface regions of the baseline vehicle with respect to the objective functions and define a proper design space with reasonable design variables. Then the EGO algorithm is applied to search for the optimal site in the design space based on the expected improvement (EI) function. Such workflow has been applied to minimize the aerodynamic drag for a mass-produced electric vehicle. With the help of STAR-CCM+ and its adjoint solver, sensitive surface regions with respect to the aerodynamic drag are first located on the vehicle.

Abstract The development of a long-term sustainable hydrogen energy economy for commercial vehicle transportation will need to overcome key critical technical and logistics considerations in the near term. As compared to zero-emission powertrains, fossil-fuel-based powertrains provide mission flexibility and high uptime at a comparatively low total cost of ownership (TCO). While the incumbent carbon-intensive powertrains suffer from poor efficiency and are not sustainable to support global climate change initiatives in transportation decarbonization, techno-economic challenges continue to create complex barriers to the large-scale displacement of these with highly electrified powertrains architectures. This article specifically addresses opportunities that well-targeted subsidies would afford in achieving fuel cell electric powertrain financial parity with diesel powertrains in heavy-duty trucks (HDTs).

Abstract The automotive industry offers many applications for machine learning (ML), in general, and deep neural networks in particular. However, the real-world deployment of neural networks into safety-critical components remains a challenge as models would need to offer robustness under a wide range of operating conditions. In this work, we focus on uncertainty estimation, which can be used to deliver predictors that fail gracefully, by detecting situations where their predictions are unreliable. Following Gräber et al. [1], we use Recurrent Neural Networks (RNNs) to perform sideslip angle estimation. To perform robust uncertainty estimation, we augment the RNNs with generative models. We demonstrate the advantage of the proposed model architecture over Monte Carlo (MC) dropout [2] on the Revs data set [3].

Abstract China is driving the transition away from internal combustion engine vehicles (ICEVs) to plug-in electric vehicles (PEVs, including plug-in hybrid electric vehicles (PHEVs) and battery electric vehicles (BEVs)) to address its pressing energy security and environmental pollution problems. The recent enactment of the dual-credit scheme mandate will compensate for the phase out of the subsidy program, while ostensibly shifting the burden of filling in the cost gap between PEVs and ICEVs from the government to the automakers (though in practice to car buyers).

Abstract The external driving environment of an autonomous driving vehicle is complex and changeable. In this article, the trajectory tracking control with obstacle avoidance based on model predictive control was presented. Specifically, double-level control scheme by controlling the front steering angle was used in our research, and the double level is composed of the high level of model predictive controller for local trajectory planning and low level of model predictive controller for trajectory tracking. At high level, the local trajectory planner based on the point-mass model was designed. Then, at low level, the linear time-varying vehicle dynamics model was presented, and the trajectory tracking controller was proposed considering control variable, control increment, and output constraint. Finally, the trajectory tracking performance was tested in co-simulation environment with CarSim and Simulink, and the tracking errors were analyzed.

Abstract This article introduces a finite element (FE) approach to determine tire deformation and its effect on open-wheel race car aerodynamics at high vehicle velocities. In recent literature tire deformation was measured optically. Combined loads like accelerating at a corner exit are difficult to reproduce in wind tunnels and require several optical devices to measure the tire deformation. In contrast, an FE approach is capable of determining the tire deformation in combined load states accurately. Additionally, the temperature influence on tire deformation is investigated. The FE tire model was validated using three-dimensional (3D) scan measurements; stiffness measurements in the vertical, lateral, and longitudinal direction; and the change of loaded radius with speed at different loads, respectively. The deformed shape of the tire of the FE model was used in a computational fluid dynamics (CFD) simulation.

Abstract To investigate the effect of a tire blowout (TBO) on the dynamics of the vehicle comprehensively, a three-dimensional full-vehicle multibody mathematical model is developed and integrated with the nonlinear Dugoff’s tire model. In order to ensure the validity of the developed model, a series of standard maneuvers is carried out and the resulting response is verified using the high-fidelity MSC Adams package. Consequently, the in-plane, as well as out-of-plane dynamics of the vehicle, is extensively examined through a sequence of TBO scenarios with various blown tires and during both rectilinear and curvilinear motion. Moreover, the different possible inputs from the driver, the road bank angle, and the antiroll bar have been accounted for. The results show that the dynamic behavior of the vehicle is tremendously affected both in-plane and out-of-plane and its directional stability is degraded.

Abstract Aircraft cybersecurity efforts have tended to focus at the strategic or tactical levels without a clear connection between the two. There are many excellent engineering tools already in widespread use, but many organizations have not yet integrated and linked them into an overarching “campaign plan” that connects those tactical actions such as process hazard analysis, threat modeling, and probabilistic methods to the desired strategic outcome of secure and resilient systems. This article presents the combined systems security engineering process (CSSEP) as a way to fill that gap. Systems theory provides the theoretical foundation on which CSSEP is built. CSSEP is structured as a control loop in which the engineering team is the controller of the design process. The engineering team needs to have an explicit process model on how systems should be secured, and a control algorithm that determines what control actions should be selected.

Abstract A novel geometry for a six degrees of freedom (6DOF) unmanned aerial vehicle (UAV) rotary wing aircraft is introduced and a flight mechanical analysis is conducted for an aircraft built in accordance to the thrust vectors of the proposed geometry. Furthermore, the necessary mathematical operations and control schemes are derived to fly an aircraft with the proposed geometry. A system identification of the used propulsion system with the necessary thrust reversal in the form of bidirectional motors and propellers was conducted at a whirl tower. The design of the first prototype aircraft is presented as well as the first flight test results. It could be demonstrated that an aircraft with the thrust vectors oriented according to the proposed geometry works sufficiently and offers unique maneuvering capabilities that cannot be reached with a conventional design.

Abstract Pyrotechnic seat belt pretensioners typically remove 8–15 cm of belt slack and help couple an occupant to the seat. Our study investigated pretensioner deployment on forward-leaning, live volunteers. The forward-leaning position was chosen because research indicates that passengers frequently depart from a standard sitting position. Characteristics of the 3D kinematics of forward-leaning volunteers following pretensioner deployment determines if body size is correlated with subject response. Nine adult subjects (three female), ages 18–43 years old, across a wide range of body sizes (50–120 kg) were tested. The age was limited to young, active adults as pyrotechnic pretensioners can deliver a notable force to the trunk. Subjects assumed a forward-leaning position, with 26 cm between C7 and the headrest, in a laboratory setting that replicated the passenger seat of a vehicle.

Abstract Formula Student Driverless (FSD) challenges engineering students to develop autonomous single-seater race cars in a quest to bring about more graduates who are well prepared to solve the real-world problems associated with autonomous driving. In this article, we present the software stack of KA-RaceIng’s entry to the 2019 competitions. We cover the essential modules of the system, including perception, localization, mapping, motion planning, and control. Furthermore, development methods are outlined, and an overview of the system architecture is given. We conclude by presenting selected runtime measurements, data logs, and competition results to provide an insight into the performance of the final prototype.

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