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With the increase of hotel and ancillary loads and replacement of engine driven mechanical and hydraulic loads with electrical loads, automotive systems are becoming more electric. This is the concept of More Electric Cars (MEC) that necessitates a higher system voltage, such as the proposed 42V, for conventional cars. In this paper, the development of the 42V electric power system for vehicle applications is reviewed. The system architecture and motor drive problems associated with the 42V electric power system are analyzed. Solutions to these problems are also discussed.

The use of virtual prototyping early in the design stage of a product has gained popularity due to reduced cost and time to market. The state of the art in vehicle simulation has reached a level where full vehicles are analyzed through simulation but major difficulties continue to be present in interfacing the vehicle model with accurate powertrain models and in developing adequate formulations for the contact between tire and terrain (specifically, scenarios such as tire sliding on ice and rolling on sand or other very deformable surfaces). The proposed work focuses on developing a ground vehicle simulation capability by combining several third party packages for vehicle simulation, tire simulation, and powertrain simulation. The long-term goal of this project consists in promoting the Digital Car idea through the development of a reliable and robust simulation capability that will enhance the understanding and control of off-road vehicle performance.

In order to reduce fuel consumption, companies have been looking at hybridizing vehicles. So far, two main hybridization options have been considered: electric and hydraulic hybrids. Because of light duty vehicle operating conditions and the high energy density of batteries, electric hybrids are being widely used for cars. However, companies are still evaluating both hybridization options for medium and heavy duty vehicles. Trucks generally demand very large regenerative power and frequent stop-and-go. In that situation, hydraulic systems could offer an advantage over electric drive systems because the hydraulic motor and accumulator can handle high power with small volume capacity. This study compares the fuel displacement of class 6 trucks using a hydraulic system compared to conventional and hybrid electric vehicles. The paper will describe the component technology and sizes of each powertrain as well as their overall vehicle level control strategies.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

Designing a vehicle for superior crash safety performance in consumer rating tests such as US-NCAP is a compelling target in the design of passenger vehicles. In today’s context, there is also a high emphasis on making a vehicle as lightweight as possible which calls for an efficient design. In modern vehicle design, these objectives can only be achieved through Computer-Aided Engineering (CAE) for which a detailed CAD (Computer-Aided Design) model of a vehicle is a pre-requisite. In the absence of the latter (i.e. a matured CAD model) at the initial and perhaps the most crucial phase of vehicle body design, a rational approach to design would be to resort to a knowledge-based methodology which can enable crash safety assessment of an assumed design using artificial intelligence techniques such as neural networks.

A methodology has been developed for identifying the combination of battery characteristics which lead to least-cost electric vehicles. Battery interrelationships include specific power vs, specific energy, peak power vs. specific energy and DOD, cycle life vs. DOD, cost vs. specific energy and peak power, and volumetric and battery size effects. The method is illustrated for the “second car” mission assuming lead/acid batteries. Reductions in life-cycle costs associated with future battery research breakthroughs are estimated using a sensitivity technique. A research prioritization system is described.

When performing trajectory planning for robotic applications, there are many aspects to consider, such as the reach conditions, joint and end-effector velocities, accelerations and jerk conditions, etc. The reach conditions are dependent on the end-effector orientations and the robot kinematic structure. The reach condition feasibility is the first consideration to be addressed prior to optimizing a solution. The ‘functional’ work space or work window represents a region of feasible reach conditions, and is a sub-set of the work envelope. It is not intuitive to define. Consequently, 2D solution approaches are proposed. The 3D travel paths are decomposed to a 2D representation via radial projections. Forward kinematic representations are employed to define a 2D boundary curve for each desired end effector orientation.

In this paper, a mild hybrid drive train has been proposed. A small electric motor with low rated voltage (42 V) is used to (1) propel the vehicle at low speed, (2) replace the fluid-coupled torque converter and (3) realize regenerative braking. With proper design and control, the fuel economy in urban driving can be significantly improved without much change from conventional drive train to the mild hybrid drive train.

Significant amount of energy is lost in frequent braking, automatic transmission and engine idling for a conventional engine powered passenger car while driving in cities. In this paper, a mild hybrid vehicle drive train has been introduced. It uses a small electric motor with floating stator, called TRANSMOTOR and small and a battery pack. The transmotor functions as a generator, engine starter, frictionless clutch (electric torque coupler), regenerative braking and propelling. The mild hybrid drive train can effectively reduce the urban-driving fuel consumption by regenerative braking, eliminate of energy losses in conventional automatic transmission and engine idling. The drive train can use low voltage system (42V for example), due to the low electric power rating, and is more similar to conventional drive train than full hybrid vehicle. Therefore, less effort is needed to evolve it from conventional vehicles.

The Modular Automotive Technology Testbed (MATT) is a flexible platform built to test different technology components in a vehicle environment. This testbed is composed of physical component modules, such as the engine and the transmission, and emulated components, such as the energy storage system and the traction motor. The instrumentation on the tool enables the energy balance for individual components on drive cycles. Using MATT, a single set of hardware can operate as a conventional vehicle, a hybrid vehicle and a plug-in hybrid vehicle, enabling direct comparison of petroleum displacement for the different modes. The engine provides measured fuel economy and emissions. The losses of components which vary with temperature are also measured.

Mobility assessment for combat vehicles is often a great challenge for the military due to various subjective attributes. The attributes' characteristics vary significantly depending on the vehicle type and its operating environments such as terrain, weather, and human factors. A clear definition and relationship between multiple attributes including human factors is necessary to assess mobility. To the best of authors' knowledge, many existing mobility assessment techniques use complex analytical methods and focus on individual attributes. In this paper, for the first time, the authors propose a novel approach to define vehicle mobility and its influencing attributes using qualitative linguistic fuzzy variables, which are defined as having values between 0 and 1. The authors also propose a fuzzy logic mobility (FLM) model and a simulation approach to assess a combat vehicle's mobility.

There are many challenges in implementing grid aware plug-in electric vehicle (PEV) charging systems with local load control. New opportunities for innovative load control were created as a result of changes to the 2014 National Electric Code (NEC) about automatic load control definitions for EV charging infrastructure. Stakeholders in optimized dispatch of EV charging assets include the end users (EV drivers), site owner/operators, facility managers and utilities. NEC definition changes allow for ‘over subscription’ of more potential EV charging station load than can be continuously supported if the total load at any time is within the supply system safety limit. Local load control can be implemented via compact submeter(s) with locally hosted control algorithms using direct communication to the managed electric vehicle supply equipment (EVSE).

Plug-in hybrid electric vehicle (PHEV) technologies have the potential for considerable petroleum consumption reductions, possibly at the expense of increased tailpipe emissions due to multiple “cold” start events and improper use of the engine for PHEV specific operation. PHEVs operate predominantly as electric vehicles (EVs) with intermittent assist from the engine during high power demands. As a consequence, the engine can be subjected to multiple cold start events. These cold start events may have a significant impact on the tailpipe emissions due to degraded catalyst performance and starting the engine under less than ideal conditions. On current hybrid electric vehicles (HEVs), the first cold start of the engine dictates whether or not the vehicle will pass federal emissions tests. PHEV operation compounds this problem due to infrequent, multiple engine cold starts.

Due to the variation of compartment design and occupant’s posture in self-driving cars, there is a new and major challenge for occupant protection. In particular, the studies on occupant restraint systems used in the self-driving car have been significantly delayed compared to the development of the autonomous technologies. In this paper, a numerical study was conducted to investigate the effectiveness of three typical restraint systems on the driver protection in three different scenarios.

As connectivity and sensing technologies become more mature, automated vehicles can predict future driving situations and utilize this information to drive more energy-efficiently than human-driven vehicles. However, future information beyond the limited connectivity and sensing range is difficult to predict and utilize, limiting the energy-saving potential of energy-efficient driving. Thus, we combine a conventional speed optimization planner, developed in our previous work, and reinforcement learning to propose a real-time intelligent speed optimization planner for connected and automated vehicles. We briefly summarize the conventional speed optimization planner with limited information, based on closed-form energy-optimal solutions, and present its multiple parameters that determine reference speed trajectories.

It is recognized that there is a dearth of studies that provide a comprehensive understanding of vehicle-occupant system dynamics for various road conditions, sitting occupancies and vehicle velocities. In the current work, an in-house-developed 50 degree-of-freedom (DOF) multi-occupant vehicle model is employed to obtain the vehicle and occupant biodynamic responses for various cases of vehicle velocities and road roughness. The model is solved using MATLAB scripts and library functions. Random road profiles of Classes A, B, C and D are generated based on PSDs (Power Spectral Densities) of spatial and angular frequencies given in the manual ISO 8608. A study is then performed on vehicle and occupant dynamic responses for various combinations of sitting occupancies, velocities and road profiles. The results obtained underscore the need for considering sitting occupancies in addition to velocity and road profile for assessment of ride comfort for a vehicle.

The passenger cabin heating and cooling has a considerable impact on the fuel economy for buses, especially during the waiting period. This problem becomes more significant for the hybrid buses for which the impact of the auxiliary load on the fuel economy is almost twice that on the conventional buses. A second-law analysis conducted in this study indicates that a heat-driven AC system has higher energy utilization efficiency than the conventional AC system. On the basis of this analysis, a concept waste-heat-driven absorptive aqua-ammonia heat pump system is proposed and analyzed. Results of the analysis show that the heat-driven system can reduce the engine auxiliary load significantly because it eliminates the conventional AC compressor. In the AC mode, its energy utilization efficiency can be up to 50%. In the heating mode, the effective efficiency for heating can be up to 100%.

This paper discusses a new computer simulation tool, V-Elph, which extends the capabilities of previous modeling and simulation efforts by facilitating in-depth studies of any type of hybrid or all electric configuration or energy management strategy through visual programming and by creating components as hierarchical subsystems which can be used interchangeably as embedded systems. V-Elph is composed of detailed models of four major types of components: electric motors, internal combustion engines, batteries, and vehicle dynamics which can be integrated to simulate drive trains having all electric, series hybrid, and parallel hybrid configurations. V-Elph was written in the Matlab/Simulink graphical simulation language and is portable to most computer platforms. A simulation study of a sustainable, electrically-peaking hybrid-electric vehicle was performed to illustrate the applicability of V-Elph to hybrid and electric vehicle design.

The transition from the multi-component ABS2 design to the one housing concept of ABS5.0 represented a significant step in improving the ABS unit. ABS5.3 is the successor of ABS5.0 to achieve a highly compact, light weight inexpensive design, for the broad use of ABS in all passenger cars and light trucks. New technologies applied are the staking technique for hydraulic components, the use of microhybrid electronics design and solenoid coils being integrated within the attached electronic control unit. The unit can be manufactured in global alliance achieved by simultaneous engineering, applying CAD, FE-analysis, flow calculation and simulation, noise analysis and quality assurance which includes FMEA, error simulation, durability tests and the dry testing concept. The ABS5.3 design can be easily expanded to Traction Control (ASR).

Environmental consciousness and tightening emissions legislation push the market share of electronic fuel injection within a dynamically growing world wide small engines market. Similar to automotive engines during late 1980's, this opens up opportunities for original equipment manufacturers (OEM) and suppliers to jointly advance small engines performance in terms of fuel economy, emissions, and drivability. In this context, advanced combustion system analyses from automotive engine testing have been applied to a typical production motorcycle small engine. The 125cc 4-stroke, 2-valve, air-cooled, single-cylinder engine with closed-loop lambda-controlled electronic port fuel injection was investigated in original series configuration on an engine dynamometer. The test cycle fuel consumption simulation provides reasonable best case fuel economy estimates based on stationary map fuel consumption measurements.