Trip-Based Optimal Power Management of Plug-in Hybrid Electric Vehicles

Hybrid electric vehicles (HEVs) have demonstrated the capability to improve fuel economy and emissions. The plug-in HEV (PHEV), utilizing more battery power, has become a more attractive upgrade of the HEV. The charge-depletion mode is more appropriate for the power management of PHEVs, i.e., the state of charge (SOC) is expected to drop to a low threshold when the vehicle reaches the trip destination. Trip information has so far been considered as future information for vehicle operation and is thus not available a priori. This situation can be changed by the recent advancement in intelligent transportation systems (ITSs) based on the use of on-board global positioning systems (GPSs), geographical information systems (GISs), and advanced traffic flow modeling techniques. In this paper, a new approach to optimal power management of PHEVs in the charge-depletion mode is proposed with driving cycle modeling based on the historic traffic information. A dynamic programming (DP) algorithm is applied to reinforce the charge-depletion control such that the SOC drops to a specific terminal value at the end of the driving cycle. The vehicle model was based on a hybrid electric sport utility vehicle (SUV). Only fuel consumption is considered for the current stage of the study. A simulation study was conducted for several standard driving cycles and two trip models using the proposed method, and the results showed significant improvement in fuel economy compared with a rule-based control and a depletion sustenance control for most cases. Furthermore, the results showed much better consistency in fuel economy compared with rule-based and depletion sustenance control.      

Development of a Scaled Vehicle With Longitudinal Dynamics of an HMMWV for an ITS Testbed

This paper applies Buckingham's pi theorem to the problem of building a scaled car whose longitudinal and power-train dynamics are similar to those of a full-size high-mobility multipurpose wheeled vehicle (HMMWV). The scaled vehicle uses hardware-in-the-loop (HIL) simulation to capture some of the scaled HMMWV dynamics physically, and simulates the remaining dynamics onboard in real time. This is performed with the ultimate goal of testing cooperative collision avoidance algorithms on a testbed comprising a number of these scaled vehicles. Both simulation and experimental results demonstrate the validity of this HIL-based scaling approach.     

Modeling of a Series Hybrid Electric High-Mobility Multipurpose Wheeled Vehicle

In an effort to reduce fuel costs and gas emissions, the U.S. Army is looking into replacing their diesel high-mobility multipurpose wheeled vehicle (HMMWV) with hybrid electric vehicles. The aim of this paper is to present the simulation of the series hybrid electric HMMWV based on a multidomain model using Ansoft Simplorer. Emphasis is placed on the vehicle's transient response to desired speeds dictated by drive cycles based on an urban dynamometer driving schedule and SAE J227a Schedule D. Also included in this paper were the vehicle's responses to hill climbing up to 60% grade     

Sliding mode based powertrain control for efficiency improvement in series hybrid-electric vehicles

This study involves the improvement of overall efficiency in series hybrid-electric vehicles (SHEVs) by restricting the operation of the engine to the optimal efficiency region, using a control strategy based on two chattering-free sliding mode controllers (SMCs). One of the designed SMCs performs engine speed control, while the other controls the engine/generator torque, together achieving the engine operation in the optimal efficiency region of the torque-speed curve. The control strategy is designed for application on a SHEV converted from a standard high mobility multipurpose wheeled vehicle (HMMWV) and simulated by using the Matlab-based PNGV Systems Analysis Toolkit (PSAT). The performance of the control strategy is compared with that of the original PSAT model, which utilizes PI controllers, a feedforward term for the engine torque, and comprehensive maps for the engine, generator and power converter (static only), which constitute the auxiliary power unit (APU). In this study, in spite of the simple modeling approach taken to model the APU and the optimal efficiency region, an improved performance has been achieved with the new SMC based strategy in terms of overall efficiency, engine efficiency, fuel economy, and emissions. The control strategy developed in this work is the first known application of SMC to SHEVs, and offers a simple, effective and modular approach to problems related to SHEVs.     

Unified modeling of hybrid electric vehicle drivetrains

Hybridizing automotive drivetrains, or using more than one type of energy converter, is considered an important step toward very low pollutant emission and high fuel economy. The automotive industry and governments in the United States, Europe, and Japan have formed strategic initiatives with the aim of cooperating in the development of new vehicle technologies. Efforts to meet fuel economy and exhaust emission targets have initiated major advances in hybrid drivetrain system components, including: high-efficiency high-specific power electric motors and controllers; load-leveling devices such as ultracapacitors and fly-wheels; hydrogen and direct-methanol fuel cells; direct injection diesel and Otto cycle engines; and advanced batteries. The design of hybrid electric vehicles is an excellent example of the need for mechatronic system analysis and design methods. If one is to fully realize the potential of using these technologies, a complete vehicle system approach for component selection and optimization over typical driving situations is required. The control problems that arise in connection with hybrid power trains are significant and pose additional challenges to power-train control engineers. The principal aim of the paper is to propose a framework for the analysis, design, and control of optimum hybrid vehicles within the context of energy and power flow analysis. The approaches and results presented in the paper are one step toward the development of a complete toolbox for the analysis and design of hybrid vehicles     

Development of a Hybrid Electric Vehicle With a Hydrogen-Fueled IC Engine

The motivation for the use of hydrogen as fuel is that it can be renewable and can reduce emissions. Hydrogen fuel cell vehicles are still likely to be more of a far-term reality because of their high manufacturing cost. A hybrid electric vehicle (HEV) with a hydrogen-fueled internal combustion (IC) engine has the potential of becoming a low-emission low-cost practical solution in the near future. This paper describes a standard sport utility vehicle (SUV) that has been converted into a hydrogen-powered HEV. The powertrain utilizes compressed gaseous hydrogen as fuel, a boosted hydrogen IC engine, an induction motor, a hydraulic transmission, regenerative braking, advanced nickel-metal hybrid batteries, and a real-time control system. Tests show that the vehicle can deliver higher fuel economy and much lower emissions than those of a traditional SUV without compromises in performance. This paper presents an overview of the prototype vehicle and emphasizes some of the unique features of this energy-saving clean environment solution     

A 42-V Electrical and Hybrid Driving System Based on a Vehicular Waste-Heat Thermoelectric Generator

A 42-V powernet has been recognized as the next generation of vehicle electrical systems, and the waste-heat thermoelectric generator is becoming the future of vehicular energy conservation and emission reduction technologies. In this paper, effective utilization of vehicular waste-heat energy is proposed by introducing an electrical and hybrid driving system, which is an assemblage of a waste-heat thermoelectric generator, a 42-V powernet, and an integrated starter and generator (ISG). A vehicle model and the submodels for the new system have been built on the ADVISOR platform based on MATLAB/Simulink, and the dynamic performance of the vehicle model tested using the Economic Commission for Europe?CEurope Urban Dynamometer Cycle driving cycle. The simulation results indicate that application of a 42-V waste-heat thermoelectric vehicle could be an integrated approach for fuel economy improvement and emission reduction, compared with a conventional internal combustion engine vehicle and an ISG-type 42-V vehicle.     

Development and Future Issues of High Voltage Systems for FCV

Nissan Motor Co., Ltd, has delivered the New X-TRAIL FCV 2005 Year Model to customers in April 2006 in Japan, in which a newly developed in-house fuel cell stack and 70-MPa high-pressure hydrogen storage system are installed. For fuel cell vehicles, not only the fuel cell system and the hydrogen storage system but also the high-voltage system is very important, such as a traction motor to propel the vehicle, motors that drive some devices for the fuel cell system, a second battery that stores braking energy and assists the acceleration, inverters which supply alternating current to the prescribed motors, and converters which change voltage generated by the fuel cell stack to the specific level for each subsystems to operate. X-TRAIL FCV 2005MY has increased the performance of driving range and acceleration compared to 2003MY. We have practiced using new technologies to reduce the size reduction of the high-voltage system to achieve these performance improvements, but it still needs many improvements to make fuel cell vehicles popular to the market     

Effects of drivetrain hybridization on fuel economy and dynamic performance of parallel hybrid electric vehicles

Hybrid electric vehicles have proved to be the most practical solution in reaching very high fuel economy as well as very low emissions. However, there is no standard solution for the optimal size or ratio of the internal combustion engine and the electric system. The optimum choice includes complex tradeoffs between the heat engine and electric propulsion system on one hand and cost, fuel economy, and performance on the other. Each component, as well as the overall system, have to be optimized to give optimal performance and durability at a low price. In this paper, we look at the effects of hybridization on fuel economy and dynamic performances of vehicles. Different hybridization levels from mild to full hybrid electric traction systems are examined. We also present the optimum level of hybridization for typical passenger cars. This study shows that low hybridization levels provide an acceptable fuel economy benefit at a low price, while the optimal level of hybridization ranges between 0.3 and 0.5, depending on the total vehicle power.     

Control Strategy for a 42-V Waste-Heat Thermoelectric Vehicle

A 42-V waste-heat thermoelectric vehicle is employed as a potential application of thermoelectric generators for fuel economy improvement and emissions reduction. The 42-V waste-heat thermoelectric vehicle currently in development employs an assemblage driving system consisting of a waste-heat thermoelectric generator, a 42-V powernet, and an integrated starter and generator (ISG). The waste-heat thermoelectric generator also functions as a power supply. To optimize the utilization of the waste-heat energy generated by the thermoelectric generator, an electric assist control strategy and a torque split control strategy are proposed herein. Through the development of relevant systems and strategies, including the thermoelectric generator and an electric bus system, two vehicle models are established and compared using the ADVISOR platform based on MATLAB/Simulink. The calculation results show improved fuel economy and emissions performance resulting from the integration of the torque split control strategy into the 42-V waste-heat thermoelectric vehicle.     

Fuzzy Gain-Scheduling Proportional–Integral Control for Improving Engine Power and Speed Behavior in a Hybrid Electric Vehicle

With the increased emphasis on improving fuel economy and reducing emissions, hybrid electric vehicles (HEVs) have emerged as very strong candidates to achieve these goals. The power-split hybrid system, which is a complex hybrid powertrain, exhibits great potential to improve fuel economy by determining the most efficient regions for engine operation and thereby high-voltage (HV) battery operation to achieve overall vehicle efficiency optimization. To control and maintain the actual HV battery power, a sophisticated control system is essential, which controls engine power and thereby engine speed to achieve the desired HV battery maintenance power. Conventional approaches use proportional-integral (PI) control systems to control the actual HV battery power in power-split HEV, which can sometimes result in either overshoots of engine speed and power or degraded response and settling times due to the nonlinearity of the power-split hybrid system. We have developed a novel approach to intelligently controlling engine power and speed behavior in a power-split HEV using the fuzzy control paradigm for better performances. To the best of our knowledge, this is the first reported use of the fuzzy control method to control engine power and speed of a power-split HEV in the applied automotive field. Our approach uses fuzzy gain scheduling to determine appropriate gains for the PI controller based on the system's operating conditions. The improvements include elimination of the overshoots as well as approximate 50% faster response and settling times in comparison with the conventional linear PI control approach. The improved performances are demonstrated through simulations and field experiments using a ford escape hybrid vehicle.     

Dynamic simulation for analysis of hybrid electric vehicle system and subsystem interactions, including power electronics

Simulation tools for hybrid electric vehicles (HEVs) can be classified into steady-state and dynamic models, according to their purpose. Tools with steady-state models are useful for system-level analysis. The information gained is helpful for assessing long-term behavior of the vehicle. Tools that utilize dynamic models give in-depth information about the short-term behavior of sublevel components. In this paper, a dynamic model of a hybrid electric vehicle that includes fuel cells, batteries, ultracapacitors, and induction machine drives is presented. Simulation results of vehicle configurations with a battery, a fuel cell-battery combination and a fuel cell-ultracapacitor combination are discussed. The focus of the model is a detailed assessment of different subsystem components, particularly component losses.     

An analysis of vehicle-to-infrastructure communications for non-signalised intersection control under mixed driving behaviour

Intersection control has an important role in the management of urban traffic to ensure safety, high traffic flow and to prevent congestion. Recently, a growing body of literature has been reported on the theme of non-signalised intersection control in which traffic lights are replaced with intelligent road side units. Data from several studies suggest that non-signalised control could reduce vehicle delays and fuel consumption significantly whilst ensuring safety. However, there is little published data on the impact of the mixed driving behaviour with human-driven vehicles and autonomous vehicles. This paper investigates the emerging role of connectivity and vehicle autonomy in the context of traffic control under the mixed driving behaviour scenario. The concepts of vehicle-to-infrastructure (V2I) communications and multi-agent systems are central to achieving a robust and reliable traffic-light-free intersection control. Comprehensive computer simulation results on a four-way intersection indicate over 96% reduced average vehicle delay and 37% less fuel consumption with the non-signalised control solution compared to the traffic light control. The outcome of this study offers some important insights into enabling cooperation between vehicles and traffic infrastructure via V2I communications, in order to make more efficient real-time decisions about traffic conditions, whilst ensuring a higher degree of safety.     

A Comparative Study of Fuel-Cell–Battery, Fuel-Cell–Ultracapacitor, and Fuel-Cell–Battery–Ultracapacitor Vehicles

Although many researchers have investigated the use of different powertrain topologies, component sizes, and control strategies in fuel-cell vehicles, a detailed parametric study of the vehicle types must be conducted before a fair comparison of fuel-cell vehicle types can be performed. This paper compares the near-optimal configurations for three topologies of vehicles: fuel-cell-battery, fuel-cell-ultracapacitor, and fuel-cell-battery-ultracapacitor. The objective function includes performance, fuel economy, and powertrain cost. The vehicle models, including detailed dc/dc converter models, are programmed in Matlab/Simulink for the customized parametric study. A controller variable for each vehicle type is varied in the optimization.     

Advanced Integrated Bidirectional AC/DC and DC/DC Converter for Plug-In Hybrid Electric Vehicles

Hybrid electric vehicle (HEV) technology provides an effective solution for achieving higher fuel economy, better performance, and lower emissions, compared with conventional vehicles. Plug-in HEVs (PHEVs) are HEVs with plug-in capabilities and provide a more all-electric range; hence, PHEVs improve fuel economy and reduce emissions even more. PHEVs have a battery pack of high energy density and can run solely on electric power for a given range. The battery pack can be recharged by a neighborhood outlet. In this paper, a novel integrated bidirectional AC/DC charger and DC/DC converter (henceforth, the integrated converter) for PHEVs and hybrid/plug-in-hybrid conversions is proposed. The integrated converter is able to function as an AC/DC battery charger and to transfer electrical energy between the battery pack and the high-voltage bus of the electric traction system. It is shown that the integrated converter has a reduced number of high-current inductors and current transducers and has provided fault-current tolerance in PHEV conversion.     

Predictive Reference Signal Generator for Hybrid Electric Vehicles

A novel model-based and predictive energy supervisory controller for hybrid electric vehicles (HEVs) is presented. Its objective is to minimize the fuel consumption (FC) of HEVs using only the information on the current state of charge (SoC) of the battery and data available from a standard onboard navigation system. This objective is achieved using a predictive reference signal generator (pRSG) in combination with a nonpredictive reference tracking controller for the battery SoC. The pRSG computes the desired battery SoC trajectory as a function of vehicle position such that the recuperated energy is maximized despite the constraints on the battery SoC. To compute the SoC reference trajectory, only the topographic profile of the future road segments and the corresponding average traveling speeds must be known. Simulation results of the proposed predictive strategy show substantial improvements in fuel economy in hilly driving profiles, compared with nonpredictive strategies. A parallel HEV is analyzed in this paper. However, the proposed method is independent of the powertrain topology. Therefore, the method is applicable to all types of HEVs.      

A window-based image processing technique for quantitative andqualitative analysis of road traffic parameters

Traffic information is an important tool in the planning, maintenance, and control of any modern transport system. Of special interest to traffic engineers are parameters of traffic flow such as volume, speed, type of vehicle, queue parameters, traffic movements at junctions, etc. Various algorithms, mainly based on background differencing techniques, have been applied for this purpose. Since background-based algorithms are very sensitive to ambient lighting conditions, they have not yielded the expectative results. In this paper, we describe a novel approach to measure traffic parameters. This approach is based on applying edge-detection techniques to the key regions or windows. This method of measuring road traffic parameters eliminates the need of a background frame, which is an essential, but unreliable technique for background-based image-detection methods. A dynamic threshold selection technique has also been introduced to select the threshold value automatically. The image process algorithm has been applied to measure basic traffic parameters such a traffic volume, types of vehicles, as well as the complex traffic parameters such as queue parameters and movements of vehicles at a traffic junction     

An Analytical Optimization Method for Improved Fuel Cell–Battery–Ultracapacitor Powertrain

Fuel-cell vehicles have the potential to revolutionize transportation. In particular, a fuel-cell vehicle using a combined battery–ultracapacitor energy storage system can provide excellent fuel economy and performance while extending the battery life due to more frequent use of the ultracapacitor. This paper first presents a new fuel cell–battery–ultracapacitor (FC–B–UC) vehicle topology. Then, a vehicle simulator is used to show that the new topology is superior to a promising FC–B–UC topology from the literature. Finally, an analytical optimization method is developed to determine the optimal battery and ultracapacitor sizes for two different options of the novel FC–B–UC topology. The optimization method seeks to maximize efficiency and minimize mass and cost of the overall system. Numerical examples are provided to validate the analytical optimization method.      

汽车超载监测系统

为了实时识别各种车型的超载车辆,该系统基于开源计算机视觉库(OpenCV),先根据车辆照片库建立车型分类器,然后使用数字摄像机拍摄进入监控区域的车辆,在视频中使用分类器识别车型,根据所识别得到的车型去查询数据库获得该车型的核载,再通过动态称重技术获得车辆的实际载重,及时判别车辆是否超载。此方法可避免过去使用统一重量衡量不同车型是否超载的弊端,并可同时免线圈测量车速。测试结果表明系统能快速准确地识别出车型。配合动态称重系统,就能实时得出所通过的车辆是否超载,对公路养护和道路交通安全有相当大的实用意义。