Novel coordinated algorithm for Traction Control System on split friction and slope road

A Traction Control System (TCS) is used to avoid excessive wheel-slip via adjusting active brake pressure and engine torque when vehicle starts fiercely. The split friction and slope of the road are complicated conditions for TCS. Once operated under these conditions, the traction control performance of the vehicle might be deteriorated and the vehicle might lack drive capability or lose lateral stability, if the regulated active brake pressure and engine torque can’t match up promptly and effectively. In order to solve this problem, a novel coordinated algorithm for TCS is brought forward. Firstly, two brake controllers, including a basic controller based on the friction difference between the two drive wheels for compensating this difference and a fuzzy logic controller for assisting the engine torque controller to adjust wheel-slip, are presented for brake control together. And then two engine torque controllers, containing a basic PID controller for wheel-slip control and a fuzzy logic controller for compensating torque needed by the road slope, are built for engine torque control together. Due to the simultaneous and accurate coordination of the two regulated variables the controlled vehicle can start smoothly. The vehicle test and simulation results on various road conditions have testified that the proposed method is effective and robust.     

Effect of regenerative braking energy on battery current balance in a parallel hybrid gasoline-electric vehicle under FTP-75 driving mode

In recent years, a hybrid electric vehicle (HEV) has been considered a successful technology. Especially, in case of a full HEV, the motor can drive the vehicle by itself at low velocity or assist the engine at high load. To improve the hybrid electric vehicle’s efficiency, a regenerative braking system is also applied to recover from kinetic energy. In this study, an experimental control apparatus was set up with a parallel hybrid electric vehicle mounted on a chassis dynamometer to measure ECU (engine control unit) and MCU (motor control unit) signals, including the current and state of charge in the battery. In order to analyze regenerative braking characteristics, user define braking driving cycle was introduced and carried out using different initial velocities and braking times. The FTP 75 driving cycle was then adapted under different initial SOC (state of charge) levels. The experiment data was analyzed in accordance with the vehicle velocity, battery current, instant SOC level, motor RPM, engine RPM, and then vehicle driving mode was decided. In case of braking driving cycle, it was observed that SOC were increased up to 1.5 % when the braking time and the velocidy were 6 second and 60 km/h, respectively. In addition, using the FTP 75 driving cycle, mode 1 was most frequently operated at SOC 65 conditions in phase 1. In phase 2, due to frequent stop-go hills, percentage of mode 1 was increase by 22 %. Eventually, despite of identity, it was shown that the characteristics of phase 3 differed from phase 1 due to the evanishment of the effects of initial SOCs.     

Novel hybrid optimal algorithm development for DC motor of Automated Manual Transmission

A novel hybrid optimal algorithm for DC motor of electro-mechanical Automated Manual Transmission (AMT) is presented. It combines non-linear time optimal controller and optimal Linear Quadratic Regulator (LQR) consequently used at different shifting stages. The working principle and dynamic characteristics of the AMT system are firstly presented, and the model of the DC motor is analyzed in detail. The non-linear time optimal controller is designed to explore the potential of the motor and minimize the gear shifting time. While the optimal LQR is then adopted at the final shifting stage to avoid overshoot and increase system robustness. Based on the position control algorithm of the actuators, the coordinated shifting control strategy is also proposed. Both simulation and vehicle test results demonstrate that, this control algorithm could decrease the shifting time and improve the shift quality effectively.     

Bayesian game-theoretic approach based on 802.11p MAC protocol to alleviate beacon collision under urban VANETs

Vehicular Ad-hoc Networks (VANETs) facilitate the broadcasting of status information among vehicles. In the IEEE 802.11p/WAVE vehicle network environment, the strict periodic beacon broadcasting of safety messages requires status advertisement to assist drivers in maintaining safety. The beacon broadcasting is required for real-time communication, and for avoiding the degradation of communication channels in high vehicular density situations. However, a periodic safety beacon in the IEEE 802.11p/WAVE standard can only transmit packets on a single channel using the MAC protocol. In high vehicular density situations, the channel becomes overloaded, thereby increasing the probability of beacon collision, and hence reducing the influx of successfully received beacons, which increases the delay. Many studies have indicated that appropriate congestion control algorithms are essential to provide efficient operation of a network. In this paper, to avoid beacon congestion, we have considered game theoretic models of wireless medium access control (MAC) where each transmitter makes individual decisions regarding their power level or transmission probability. We have evaluated the equilibrium transmission strategies of both the selfish and the cooperative user. In such a game-theoretic study, the central question is whether Bayesian Nash equilibrium (BNE) exists, and if so, whether the network operates efficiently at the equilibrium point. We proved that there exists only one BNE point in our game and validated our result using simulation. The performance of the proposed scheme is illustrated with the help of simulation results.     

Effect of injection timing,injector opening pressure,injector nozzle geometry,and swirl on the performance of a direct injection,compression-ignition engine fuelled with honge oil methyl ester (HOME)

Increasing petroleum prices, increasing threat to the environment from exhaust emissions and global warming have generated intense international interest in developing renewable and alternative non-petroleum fuels for engines. Evolving feasible technology and recurring energy crisis necessitated a continued investigation into the search for sustainable and clean-burning renewable fuels. In this investigation, Honge oil methyl ester (HOME) was used in a four stroke, single cylinder diesel engine. Tests were carried out to study the effect of fuel injection timing, fuel injector opening pressure (IOP) and injector nozzle geometry on the performance and combustion of CI engine fuelled with HOME. Injection timing was varied from 19°bTDC (before top dead centre) to 27°bTDC in incremental steps of 4°bTDC; injector opening pressure was varied from 210 bar to 240 bar in steps of 10 bar. Nozzle injectors of 3, 4 and 5 holes, each of 0.2, 0.25 and 0.3 mm size were selected for the study. It was concluded that retarded injection timing of 19°bTDC, increased injector opening pressure of 230 bar and 4 hole nozzle injector of 0.2 mm size resulted in overall better engine performance with increased brake thermal efficiency (BTE) and reduced HC, CO, smoke emissions. Further air-fuel mixing was improved using swirl induced techniques which enhanced the engine performance as well.     

Design and simuation of a vehicle test bed based on intelligent transport systems

As growing demand of vehicle safety system, especially regarding intelligent transport systems (ITS), automotive manufacturers are focusing more on driving safety and efficient transportation for vehicle users. Many safety systems have been launched in the market recently so, it is important to evaluate the vehicle safety systems and ITS. The ITS based intelligent vehicle test bed was constructed to meet the growing demand of test and verification for such ADAS and ITS systems. First, this paper describes in detail concept of the test-bed. This test-bed is carefully designed to meet the requirements of ISO/TC204 standards. In order to verify the design of the test-bed, virtual test with driving siulator was processed on a virtual test tracks. This test-bed will be used to conduct testing on various ITS and ADAS technologies, such as adaptive cruise control (ACC), lane departure warning system (LDWS), cooperative intersection warning system as well as rollover stability control (RSC) and electronic stability control (ESC), etc.     

Shape design optimization of interior permanent magnet motor for vibration mitigation using level set method

This paper presents a new optimization method to obtain the structural design of permanent magnet motor which can reduce the mechanical vibration. The optimization problem is formulated to minimize a multi-objective function including the mean compliance of the whole stator for maximizing the stiffness under the magnetic force and the torque ripple by aligning torque profiles to a constant target value for maximizing the magnetic performance, with constraint for material usage. The level set function is introduced for representing the structural boundaries and calculating the material properties. A coupled magneto-mechanical analysis is performed to verify the vibration characteristic of the motor system and obtain the design sensitivities. To confirm the usefulness of the proposed design method and to obtain the optimum structural design for low vibration motor, a design example of 20 kW interior permanent magnet motor developed for the power train of a hybrid electric vehicle is provided.     

Novel large scale simulation process to support dot’s cafe modeling system

This paper demonstrates a new process that has been specifically designed for the support of the U.S. Department of Transportation’s (DOT’s) Corporate Average Fuel Economy (CAFE) standards. In developing the standards, DOT’s National Highway Traffic Safety Administration made use of the CAFE Compliance and Effects Modeling System (the “Volpe model” or the “CAFE model”), which was developed by DOT’s Volpe National Transportation Systems Center for the 2005–2007 CAFE rulemaking and has been continuously updated since. The model is the primary tool used by the agency to evaluate potential CAFE stringency levels by applying technologies incrementally to each manufacturer’s fleet until the requirements under consideration are met. The Volpe model relies on numerous technology-related and economic inputs, such as market forecasts, technology costs, and effectiveness estimates; these inputs are categorized by vehicle classification, technology synergies, phase-in rates, cost learning curve adjustments, and technology “decision trees”. Part of the model’s function is to estimate CAFE improvements that a given manufacturer could achieve by applying additional technology to specific vehicles in its product line. A significant number of inputs to the Volpe decision-tree model are related to the effectiveness (fuel consumption reduction) of each fuel-saving technology. Argonne National Laboratory has developed a fullvehicle simulation tool named Autonomie, which has become one of the industry’s standard tools for analyzing vehicle energy consumption and technology effectiveness. Full-vehicle simulation tools use physics-based mathematical equations, engineering characteristics (e.g., engine maps, transmission shift points, and hybrid vehicle control strategies), and explicit drive cycles to predict the effectiveness of individual and combined fuel-saving technologies. The Large-Scale Simulation Process accelerates and facilitates the assessment of individual technological impacts on vehicle fuel economy. This paper will show how Argonne efficiently simulates hundreds of thousands of vehicles to model anticipated future vehicle technologies.     

Development of route information based driving control algorithm for a range-extended electric vehicle

A route information based driving control algorithm was developed for an RE-EV which consists of two motorgenerators, MG1 and MG2. A threshold power which controls the engine on/off to charge the battery was obtained by an optimization process using route information, such as the vehicle velocity and altitude. The threshold power allows the vehicle to travel to the final destination while making the final battery SOC close to SOC _low. Using the threshold power, route based control (RBC) was proposed by considering the driver’s characteristics and traffic conditions using the driving data base. In addition, a relationship between the threshold power and various initial battery SOC was obtained by off-line optimization. The performance of the RBC was evaluated by simulation and human-in-the-loop simulation (HILS) for city driving. It was found from the simulation and HILS results that the RBC achieved approximately 4 % to 12 % reduction in fuel consumption compared to the existing charge depleting/charge sustaining (CD/CS) driving control.     

Improving multi-channel wave-based V2X communication to support advanced driver assistance system (ADAS)

The advent of vehicle-to-everything (V2X) communication has opened the opportunity to design advanced driver assistance systems (ADAS) that collect information from sensors in neighboring vehicles and roadside infrastructure. IEEE and ETSI have designed network protocol standards for V2X communications. Despite the differences between the vehicular wireless communication architecture defined by ETSI and the IEEE protocol stack, the two standards have multichannel operations as a main commonality, with some channels dedicated to safety-critical applications and others to nonsafety services. Some recent studies have demonstrated that these standards might not provide sufficient channel utilization for reliable exchange of information in mid- and heavily congested scenarios. In this paper, we propose and evaluate the performance of a driver-assistance system to reduce the connectivity gaps between vehicles and roadside units (RSUs). This cooperative system of multi-service channel allocation will improve radio channel utilization. We also show that the required latency for this inter-vehicle communication can be obtained using the IEEE-WAVE standards and dedicated short-range communication (DSRC) proposed for vehicular environments. Simulation results show that the proposed scheme can improve the average throughput by up to 15 % in various traffic density conditions compared with the dynamic channel allocation method.