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Journal Article

Development of a Standard Testing Method for Vehicle Cabin Air Quality Index

Abstract Vehicle cabin air quality depends on various parameters such as number of passengers, fan speed, and vehicle speed. In addition to controlling the temperature inside the vehicle, HVAC control system has evolved to improve cabin air quality as well. However, there is no standard test method to ensure reliable and repeatable comparison among different cars. The current study defined Cabin Air Quality Index (CAQI) and proposed a test method to determine CAQI. CAQIparticles showed dependence on the choice of metrics among particle number (PN), particle surface area (PS), and particle mass (PM). CAQIparticles is less than 1 while CAQICO2 is larger than 1. The proposed test method is promising but needs further improvement for smaller coefficient of variations (COVs).
Journal Article

A Combination of Intelligent Tire and Vehicle Dynamic Based Algorithm to Estimate the Tire-Road Friction

Abstract One of the most important factors affecting the performance of vehicle active chassis control systems is the tire-road friction coefficient. Accurate estimation of the friction coefficient can lead to better performance of these controllers. In this study, a new three-step friction estimation algorithm, based on intelligent tire concept, is proposed, which is a combination of experiment-based and vehicle dynamic based approaches. In the first step of the proposed algorithm, the normal load is estimated using a trained Artificial Neural Network (ANN). The network was trained using the experimental data collected using a portable tire testing trailer. In the second step of the algorithm, the tire forces and the wheel longitudinal velocity are estimated through a two-step Kalman filter. Then, in the last step, using the estimated tire normal load and longitudinal and lateral forces, the friction coefficient can be estimated.
Journal Article

Development of a Learning Capability in Virtual Operator Models

Abstract This research developed methods for a virtual operator model (VOM) to learn the optimal control inputs for operation of a virtual excavator. Virtual design, used to model, simulate, and test new features, has often been limited by the fidelity of the virtual model of human operators. Human operator learns, over time, the capability, limits, and control characteristics of new vehicles to develop the best strategy to maximize the efficiency of operation. However, VOMs are developed with fixed strategies and for specific vehicle models (VMs) and require time-consuming re-tuning of the VOM for each new vehicle design. Thus, there typically is no capability to optimize strategies, taking account of variation in vehicle capabilities and limitations. A VOM learning capability was developed to optimize control inputs for the swing-to-pile task of a trenching operation. Different control strategies consisted of varied combinations of speed control, position control, and coast.
Journal Article

Improving Vehicle Rollover Resistance Using Fuzzy PID Controller of Active Anti-Roll Bar System

Abstract The active anti-roll bar (AARB) system in vehicles has recently become one of the research hotspots in the field of vehicle technology to improve the vehicle’s active safety. In most off-road vehicles, high ground clearance is required while keeping all wheels in contact with the ground in order to improve traction and maintain load distribution among the wheels. A problem however arises in some types of the off-road vehicles when the vehicle is operated at high speeds on smooth roads. In such condition, the combination of the vehicle’s center of gravity position, large suspension stroke, and soft spring construction creates a stability problem, which could make the vehicle liable to rollover. This article analyzes a comparison of stability performance between passive and active anti-roll bar systems to improve rolling resistance. For active systems, two control strategies will be investigated. The conventional PID controller is firstly investigated and taken as a reference.
Journal Article

Influence of Intelligent Active Suspension System Controller Design Techniques on Vehicle Braking Characteristics

Abstract This article presents a comprehensive investigation for the interaction between vehicle ride vibration control and braking control using two degrees of freedom (2DOF) quarter vehicle model. A typical limited bandwidth active suspension system with nonlinear spring and damping characteristics of practical hydraulic and pneumatic components is controlled to regulate both suspension and tire forces and therefore provide the optimum ride comfort and braking performance of an anti-lock brake system (ABS). In order to design a suitable controller for this nonlinear integrated system, various control techniques are followed including state feedback tuned using Linear Quadratic Regulator (LQR), state feedback tuned using Genetic Algorithm (GA), Proportional Integrated (PI) tuned genetically, and Fuzzy Logic Control (FLC). The ABS control system is designed to limit skid ratio below threshold of 15%.
Journal Article

PSO-Fuzzy Gain Scheduling of PID Controllers for a Nonlinear Half-Vehicle Suspension System

Abstract The present article addresses the gain scheduling of proportional-integral-differential (PID) controllers using fuzzy set theory coupled with a metaheuristic optimization technique to control the vehicle nonlinear suspension system. The nonlinearities of the vehicle suspension system are due to the asymmetric piecewise dampers, quadratic tire stiffness, and the cubical spring stiffness. Conventional PID controller suffers from the low performance subject to modeling nonlinearities, while fuzzy logic controller (FLC), as a universal approximator, has the capacity to deal with the nonlinear, stochastic, and complex models. However, finding the optimal Mamdani FLC rules is still a challenging task in addition to a proper architecture of the membership functions (MFs). As a remedy to this drawback, particle swarm optimization (PSO) technique is employed in this article to improve the efficiency of the FLC-based PID controllers.
Journal Article

Development of a Catalytic Converter Cool-Down Model to Investigate Intermittent Engine Operation in HEVs

Abstract Catalytic converters, a primary component in most automotive emissions control systems, do not function well until they are heated substantially above ambient temperature. As the primary energy for catalyst heating comes from engine exhaust gases, plug-in hybrid electric vehicles (PHEVs) that have the potential for short and infrequent use of their onboard engine may have limited energy available for catalytic converter heating. This article presents a comparison of multiple hybrid supervisory control strategies to determine the ability to avoid engine cold starts during a blended charge-depleting propulsion mode. Full vehicle and catalytic converter simulations are performed in parallel with engine dynamometer testing in order to examine catalyst temperature variations during the course of the US06 City drive cycle. Emissions and energy consumption (E&EC) calculations are also performed to determine the effective number of engine starts during the drive cycle.
Journal Article

Hydro-Pneumatic Energy Harvesting Suspension System Using a PSO Based PID Controller

Abstract In this article, a unique design for Hydro-Pneumatic Energy Harvesting Suspension HPEHS system is introduced. The design includes a hydraulic rectifier to maintain one-way flow direction in order to obtain maximum power generation from the vertical oscillation of the suspension system and achieve handling and comfort car drive. A mathematical model is presented to study the system dynamics and non-linear effects for HPEHS system. A simulation model is created by using Advanced Modeling Environment Simulations software (AMEsim) to analyze system performance. Furthermore, a co-simulation platform model is developed using Matlab-Simulink and AMEsim to optimize the PID controller parameters of the external variable load resistor applied on the generator by using Particle Swarm Optimization (PSO).
Journal Article

Optimization Control for 4WIS Electric Vehicle Based on the Coincidence Degree of Wheel Steering Centers

Abstract The steering centers of four wheels for passenger car do not coincide, which may result in tire wear and the unharmoniously movement of the vehicle. In this article, an optimization control method for Four Wheel Independent Steering (4WIS) electric vehicle based on the coincidence degree of steering centers is proposed, to improve the driving performance. The nonlinear vehicle model of the four-wheel independent steering vehicle is established, and the formula of the wheel steering center is derived. The coincidence degree of wheel steering centers is defined as the evaluation index, to describe and evaluate the performance of the coordination for wheels’ movement. Meanwhile, the structure design of 4WIS system and the establishment of Direct-Current (DC) steering motor model are carried out, and the Model Predictive Control (MPC) controller for steering actuator is designed.
Journal Article

Intelligent Transportation System Security: Hacked Message Signs

Abstract “It cannot happen to us” is one of many common myths regarding cybersecurity in the transportation industry. The traditional view that the threats to transportation are low probability and low impact keep agencies from mitigating security threats to transportation critical infrastructure. Current transportation systems depend on closed proprietary systems, which are enhanced by connected cyber-physical systems. Variable Message Signs (VMS) deliver advisory information to road users to ensure safe and efficient trips. Since the first VMS physical hacking more than a decade ago, the importance of VMS security has been a pressing one. VMS hacks can include physical and remote breaches due to the weak protection of the signs and cyber-physical systems.
Journal Article

A Robust Wheel Slip Control Design with Radius Dynamics Observer for EV

Abstract In order to improve the safety and dynamic performance of electric vehicles equipped with four in-wheel electric motors, and prevent the wheels from locking or slipping when braking or accelerating, a new longitudinal control strategy which combines ASR traction and ABS braking control is proposed using an observation algorithm of effective radius for four wheel of electric vehicle. Using the electric motor torques as the unique actuator signal sources, this combined ASR/ABS can act as acceleration slip regulation (ASR) by preventing the wheels from slipping during acceleration and as an antilock braking system (ABS) by preventing the wheels from getting locked during braking. A variation of effective radius of the wheel’s tire can have an incidence on the longitudinal and lateral control.
Journal Article

Adaptive Transmission Shift Strategy Based on Online Characterization of Driver Aggressiveness

Abstract Commercial vehicles contribute to the majority of freight transportation in the United States. They are also significant fuel consumers, with over 23% of fuel used in transportation in the United States. The gas price volatility and increasingly stringent regulation on greenhouse-gas emissions have driven manufacturers to adopt new fuel-efficient technologies. Among others, an advanced transmission control strategy, which can provide tangible improvement with low incremental cost. In the commercial sector, individual drivers have little or no interest in vehicle fuel economy, contrary to fleet owners. Aggressive driving behavior can greatly increase the real-world vehicle fuel consumption. However, the effectiveness of transmission calibration to match the shift strategy to the driving characteristics is still a challenge.