<p> The objective of this research is to develop an integrated system engineering methodology for the customization design to maximize vehicle performance upgrade freedom while ensuring vehicle dynamics compliance.</p><p> A post-delivery modification framework, which is led by an aftermarket umbrella organization and involve various stakeholders has been established. The umbrella organization will be in charge of developing the design envelope and distribute to various aftermarket kit suppliers to generate specific products according to their brand essence.</p><p> A generic mathematical representation of a (proprietary) ESC system has been developed for virtual certification purposes. This approach is a cost-effective alternative to physical on-road testing and hardware-in-the-loop (HiL) simulations. Furthermore, based on the stability control model, the modification impacts on the vehicle dynamics and stability performance was assessed using the Taguchi design of experiment (DOE) method. DOE results provide three distinct ways for supporting aftermarket modifications. First, main effects help customizers to understand which modification bring benefits or risks. Second, a regression model of the lateral offset metrics helps suppliers to predict closed-loop performances with open-loop testing information which require much less time and cost. Finally, the pass/fail criteria regarding federally mandated ESC compliance (FMVSS 126) brought on the &lsquo;Pass Region&rsquo; which consisted of feasible configurations such that customizers may configure their options within a safe zone. Each of these methods complements others for supporting the aftermarket modification.</p><p> In order to improve the computation efficiency, two lower fidelity models were developed: A linear model and a surrogate model. The linear model is derived from the high fidelity model with reduced degrees of freedom (DOF) and linearized parameters. Tire cornering stiffness is treated as constants for gentle maneuvers, and varying parameters for high-dynamic driving maneuver. The linear system is either a linear time-invariant (LTI) system or a linear parameter-varying (LPV) system depending on the application context. The PD yaw stability control algorithm, which is inherited from the high fidelity model, was simplified but retained with critical nonlinear features. A quadratic regression model that was dedicated for compliance metrics was developed as a surrogate model incorporated in an interactive rule-based design envelope. </p><p> An interactive design envelope has been created incorporating the rules established using computational efficient linear and surrogate models. The constraint satisfaction problem is described in the nonlinear programming context and solved using sequential quadratic programming. The quasiconvexity of the design space, which is the necessary condition for the proposed approach, is also investigated by inspecting the constraint functions. Finally, two case studies were developed to demonstrate the framework developed which was validated against the high fidelity co-simulation model.</p>

abstract: In large modern urban areas, traffic congestion and fatality have become two serious problems. To improve the safety and efficiency of ground mobility, one promising solution is the cooperative control of connected and automated vehicle (CAV) systems, which can avoid human drivers’ incapability and errors. Taking advantage of two-dimensional (2D) vehicular control, this dissertation intends to conduct a thorough investigation of the modeling, control, and optimization of CAV systems with flocking control. Flocking is a dynamic swarm congregating behavior of a group of agents with self-organizing features, and flocking control of CAV systems attempts to achieve the maintenance of a small and nearly constant distance among vehicles, speed match, destination cohesion, and collision and obstacle avoidance. Concerning artificial multi-agent systems, such as mobile robots and CAV systems, a set of engineering performance requirements should be considered in flocking theory for practical applications. In this dissertation, three novel flocking control protocols are studied, which consider convergence speed, permanent obstacle avoidance, and energy efficiency. Furthermore, considering nonlinear vehicle dynamics, a novel hierarchical flocking control framework is proposed for CAV systems to integrate high-level flocking coordination planning and low-level vehicle dynamics control together. On one hand, using 2D flocking theory, the decision making and motion planning of engaged vehicles are produced in a distributed manner based on shared information. On the other hand, using the proposed framework, many advanced vehicle dynamics control methods and tools are applicable. For instance, in the low-level vehicle dynamics control, in addition to path trajectory tracking, the maintenance of vehicle later/yaw stability and rollover propensity mitigation are achieved by using additional actuators, such as all-wheel driving and four-wheel steering, to enhance vehicle safety and efficiency with over-actuated features. Co-simulations using MATLAB/Simulink and CarSim are conducted to illustrate the performances of the proposed flocking framework and all controller designs proposed in this dissertation. Moreover, a scaled CAV system is developed, and field experiments are also completed to further demonstrate the feasibility of the proposed flocking framework. Consequently, the proposed flocking framework can successfully complete a 2D vehicular flocking coordination. The novel flocking control protocols are also able to accommodate the practical requirements of artificial multi-agent systems by enhancing convergence speed, saving energy consumption, and avoiding permanent obstacles. In addition, employing the proposed control methods, vehicle stability is guaranteed as expected. / Dissertation/Thesis / Doctoral Dissertation Systems Engineering 2020

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Nowadays, occupant safety becomes one of the most important research area and the automotive industry increased their efforts for enhancing the safety of the vehicles. The aim of this research is to investigate the effect of vehicle dynamics control systems (VDCS) on both the collision of the vehicle body and the kinematics behaviour of the vehicle’s occupant. In this work, a novel vehicle dynamics/crash mathematical model is proposed and developed to co-simulate the crash event with the VDCS. This model is achieved using the novel approach of integrating front-end structure and vehicle dynamics mathematical models. The proposed mathematical model integrates both anti-lock braking systems (ABS) and active suspension control (ASC) systems alongside with crash structure modelling. This model is developed by generating its equations of motion and solving them numerically, this approach is used due to its quick and accurate analysis. In addition, a new multi-body occupant mathematical model is developed to capture the occupant kinematics before and during the collision. Validations of the proposed mathematical models are achieved to ensure their accuracy by comparing the simulated results with other real crash test data and former models results. The validation analysis of the vehicle and occupant models shows that the comparison results are well matched and the models are valid and can be used for different crash scenarios. The numerical simulation results are divided into two parts for vehicle and occupant models, respectively. Related to the vehicle model, it is shown that the mathematical model is flexible and useful for optimization studies. The results show that the deformation of the front-end structure is reduced, the vehicle body pitching and yawing angles are notably reduced, and the vehicle pitching acceleration is greatly reduced. Related to the occupant model, it is shown that the VDCS does have a significant effect on the rotations of the occupant's chest and head owing to its effect on the vehicle pitching. In addition, the occupant's deceleration is also slightly decreased and the occupant safety is improved.

<p> This thesis focuses upon using a high-order finite-difference method on a structured overset grid to study flow features around a generic simplified car model adjusting mesh refinements, rear slant angles, solvers, and turbulence models. These processes are explored to develop a procedure for simulating more complex and realistic car models. Three different mesh refinements from 17 to 108 million vertices were tested with three different solvers (RANS, URANS, and DES) on an Ahmed body with a subcritical slant angle ascertain the optimum mesh parameters for subsequent simulations. Using a 57 x 10⁶ vertex mesh, multiple rear slant angles near the critical angle (30 degrees) were investigated with RANS and URANS approaches to compare drag, lift, and flow fields with experimental and CFD data found in literature. Similar trends were observed in CFD predictions and experimental data, including flow separation at the critical angle (30 degrees), but all predicted results were within 15% of experimental measurements for both time-averaged and unsteady simulations. At the sub-critical angle (25 degrees), CFD predictions using multiple hybrid RANS/LES approaches were compared against time-averaged and unsteady experimental measurements. These did not disagree with previous results and drag values were over predicted by a maximum of 4%, while lift values were under predicted by a maximum of 15% when compared to experimental results. Subsequent studies investigating elongated mesh refinement areas were inconclusive. The procedures outlined compare reasonably well to experimental data and can be used as a starting point for simulating more realistic models including complex dynamic pitch, heave, and roll simulations involving road vehicles.</p>

<p>The Formula SAE Electric competition is a collegiate autocross event in which teams design, build, and race an open-wheeled electric race car. The main motivation is the efficiency advantage of electric motors over internal combustion motors. This thesis presents the design and evaluation of two generations of Portland State University electric race cars. </p><p> The constraints are the competition rules, finances, human resources, and time required to complete a race car in one year. The design includes the implementation of existing components: battery cells, controllers, electric motors, drivetrains, and tire data for an optimized race car. Also, several circuits were designed and built to meet the rules, including the shutdown, precharge, discharge, brake system plausibility, tractive system active light, and an electric vehicle control unit. </p><p> The car&rsquo;s performance was modeled with calculations and OptimumLap simulation software, then track tested for actual data. Performance data such as torque, power, and temperatures were logged, and the Formula SAE events were tested. The data were compared to the simulations and records from past competitions, and the car was 21% to 30% behind the best times. </p><p> The motor generated 410 Nm of peak torque, as expected, but the maximum power was 51 kW, 15% less than the calculated 60 kW. Compared to the best times of past competitions, the car completed Skid-pad in 6.85 seconds (21% slower), and Acceleration in 5.65 seconds (25% slower). The first generation car was tested for range, and raced 31.4 km on a cold, wet track, so tire forces were decreased 6% to 69% from a dry track. During the 22 km Endurance test with the second generation car, there were problems with imbalanced cell voltages, limiting the test to 4.9 km. Later, there was a catastrophic drivetrain failure, and Endurance testing on a dry track was not completed. </p><p> In dynamic event simulations, a lighter, axial flux permanent magnet synchronous motor with a decreased counter EMF yielded improved times. Reconfiguring the battery pack from 200 <i>V_DC</i> 300 <i>V_DC</i> would provide 50% more peak power. Further testing is required to determine the actual average power use and making design decisions with an improved battery pack. </p>

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Interest in hybrid electric vehicles (HEVs) and electric vehicles (EVs) has increased rapidly over recent years from both industrial and academic viewpoints due to increasing concerns about environmental pollution and global oil usage. In the automotive sector, huge efforts have been invested in vehicle technology to improve efficiency and reduce carbon emissions with, for example, hybrid and electric vehicles. This thesis focuses on one design area of these vehicles – the transmission – with the aim of investigating the potential benefits of improved transmissions for HEVs and EVs. For HEVs, a novel transmission developed by Nexxtdrive based on a twin epicyclic design is analysed using a matrix method and its performance is compared with the more common single epicyclic arrangement used successfully in the Toyota Prius. Simulation models are then used to compare the performance of a typical HEV passenger car fitted with these two transmissions over standard driving cycles. The conclusion is that the twin epicyclic offers substantial improvements of up to 20% reduction in energy consumption, though the benefits are sensitive to the driving cycle used. For EVs, most designs to date have used a single fixed ratio transmission, and surprisingly little research has explored whether multi-geared transmissions offer any benefits. The research challenge is whether it is possible to optimise the usage of the electric motor in its region of high efficiency by controlling the transmission. Simulation results of two EV examples confirm that energy consumption benefits are indeed achievable – of between 7 and 14% depending on the driving cycle. Overall, the original aspects of this work – the analysis and modelling the twin epicyclic gearbox; the analysis and modelling the twin epicyclic system in a vehicle and a comparison of the results with single epicyclic system; and the analysis and modelling of EVs with and without a transmission system of varying levels of complexity – have shown that there are worthwhile performance benefits from using improved transmission designs for low carbon vehicles.