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The definition of the energy management strategy for a hybrid electric vehicle is a key element to ensure maximum energy efficiency. The ability to optimally manage the on-board energy sources, i.e., fuel and electricity, greatly affects the final energy consumption of hybrid powertrains. In the case of plug-in series-hybrid architectures, such as Range-Extender Electric Vehicles (REEVs), fuel efficiency optimization alone can result in a stressful operation of the range-extender engine with an excessively high number of start/stops. Nonetheless, reducing the number of start/stops can lead to long periods in which the engine is off, resulting in the after-treatment system temperature to drop and higher emissions to be produced at the next engine start.

Typically, when one thinks of advanced driver assistance systems (ADAS), systems such as Forward Collision Warning (FCW) and Collision Imminent Braking (CIB) come to mind. In these systems driver assistance is provided based on knowledge about the subject vehicle and surrounding objects. A new class of these systems is being implemented. These systems not only use information on the surrounding objects but also use information on the driver's response to an event, to determine if intervention is necessary. As a result of this trend, an advanced level of understanding of driver braking behavior is necessary. This paper presents an alternate method of analyzing driver braking behavior. This method uses a frequency content based approach to study driver braking and allows for the extraction of significantly more data from driver profiles than traditionally would have been done.

Improvements in highway fuel economy require clever design and novel methods to reduce the drag coefficient. The integration of active flow control devices into vehicle design shows promise for greater reductions in drag coefficient. This paper examines the use of fluidic oscillators for separation control at the rear of an Ahmed vehicle model. A fluidic oscillator is a simple device that generates a sweeping jet output, similar to some windshield wiper spray nozzles, and is increasingly recognized as an efficient means to control separation. In this study, fluidic oscillators were used to blow unsteady air jets and control flow separation on rear boat-tail flaps, achieving drag reductions greater than 70 counts. The method appears to scale favorably to a larger model, and realistic effects such as a rolling road appear to have a small impact on the oscillator's control authority.

Engine downsizing and super/turbocharging is currently the most followed trend in order to reduce CO2 emissions and increase the powertrain efficiency. A key challenge for achieving the desired fuel economy benefits lies in optimizing the design and control of the engine boosting system, which requires the ability to rapidly sort different design options and technologies in simulation, evaluating their impact on engine performance and fuel consumption. This paper presents a scalable modeling approach for the characterization of flow and efficiency maps for automotive turbochargers. Starting from the dimensional analysis theory for turbomachinery and a set of well-known control-oriented models for turbocharged engines simulation, a novel scalable model is proposed to predict the flow and efficiency maps of centrifugal compressors and radial inflow turbines as function of their key design parameters.

With the current drive of automotive and technology companies towards producing vehicles with higher levels of autonomy, it is inevitable that there will be an increasing number of SAE level L4-L5 autonomous vehicles (AVs) on roadways in the near future. Microscopic traffic simulators that simulate realistic traffic flow are crucial in studying, understanding and evaluating the fuel usage and mobility effects of having a higher number of autonomous vehicles (AVs) in traffic under realistic mixed traffic conditions including both autonomous and non-autonomous vehicles. In this paper, L4-L5 AVs with varying penetration rates in total traffic flow were simulated using the microscopic traffic simulator Vissim on urban, mixed and freeway roadways. The roadways used in these simulations were replicas of real roadways in and around Columbus, Ohio, including an AV shuttle routes in operation.

Dynamic programming (DP) has been used for optimal control of hybrid powertrain and vehicle speed optimization particularly in design phase for over a couple of decades. With the advent of autonomous and connected vehicle technologies, automotive industry is getting closer to implementing predictive optimal control strategies in real time applications. The biggest challenge in implementation of optimal controls is the limitation on hardware which includes processor speed, IO speed, and random access memory. Due to the use of autonomous features, modern vehicles are equipped with better onboard computational resources. In this paper we present a comparison between multiple hardware options for dynamic programming. The optimal control problem considered, is the optimization of travel time and fuel economy by tuning the torque split ratio and vehicle speed while maintaining charge sustaining operation.

The injury outcome of a front-front two-vehicle crash will be a function of crash-specific, vehicle-specific, and occupant-specific parameters. This paper focuses on a preliminary methodology that was used to evaluate the potential for benefits in making vehicle-specific changes to improve the compatibility of light vehicles across the fleet. In particular, the effect on injury rates of matching vehicle frontal stiffness was estimated. The front-front crash data for belted drivers in the lighter vehicles in the crash from ten years of NASS-CDS data were examined. The frontal stiffness of each vehicle was calculated using data taken during full frontal rigid barrier tests for the U.S. New Car Assessment Program (NCAP), and only crashes coded in the CDS as “no override” were considered.

Simulation-based design of connected and automated hybrid-electric vehicles is a challenging problem. The design space is large, the systems are complex, and the influence of connected and autonomous technology on the process is a new area of research. The Ohio State University EcoCAR Mobility Challenge team developed a comprehensive design and simulation approach as a solution. This paper covers the detailed simulation work conducted after initial design space reduction was performed to arrive at a P0-P4 hybrid vehicle with a gasoline engine. Two simulation environments were deployed in this strategy, each with unique advantages. The first was Autonomie, which is a commercial software tool that is well-validated through peer-reviewed studies. This allowed the team to evaluate a wide range of components in a robust simulation framework.

In recent years, the trend in the automotive industry has been favoring the reduction of fuel consumption in vehicles with the help of new and emerging technologies, such as Vehicle to Infrastructure (V2I), Vehicle to Vehicle (V2V) and Vehicle to Everything (V2X) communication and automated driving capability. As the world of transportation gets more and more connected through these technologies, the need to implement algorithms with V2I capability is amplified. In this paper, an algorithm called Pass at Green, utilizing V2I and vehicle longitudinal automation to modify the speed profile of a mid-size generic vehicle to decrease fuel consumption has been studied. Pass at Green (PaG) uses Signal Phase and Timing (SPaT) information acquired from upcoming traffic lights, which are the current phase of the upcoming traffic light and remaining time that the phase stays active.

This paper presents a cohesive set of engine-in-the-loop (EIL) studies examining the use of hierarchical model-predictive control for fuel consumption minimization in a class-8 heavy-duty truck intended to be equipped with Level-1 connectivity/automation. This work is motivated by the potential of connected/automated vehicle technologies to reduce fuel consumption in both urban/suburban and highway scenarios. The authors begin by presenting a hierarchical model-predictive control scheme that optimizes multiple chassis and powertrain functionalities for fuel consumption. These functionalities include: vehicle routing, arrival/departure at signalized intersections, speed trajectory optimization, platooning, predictive optimal gear shifting, and engine demand torque shaping. The primary optimization goal is to minimize fuel consumption, but the hierarchical controller explicitly accounts for other key objectives/constraints, including operator comfort and safe inter-vehicle spacing.

The EcoCAR 2: Plugging into the Future team at the Ohio State University is designing a Parallel-Series Plug-in Hybrid Electric Vehicle capable of 50 miles of all-electric range. The vehicle features a 18.9-kWh lithium-ion battery pack with range extending operation in both series and parallel modes made possible by a 1.8-L ethanol (E85) engine and 6-speed automated manual transmission. This vehicle is designed to drastically reduce fuel consumption, with a utility factor weighted fuel economy of 75 miles per gallon gasoline equivalent (mpgge), while meeting Tier II Bin 5 emissions standards. This report details the rigorous design process followed by the Ohio State team during Year 1 of the competition. The design process includes identifying the team customer's needs and wants, selecting an overall vehicle architecture and completing detailed design work on the mechanical, electrical and control systems. This effort was made possible through support from the U.S.

Recently there has been a greater awareness of the increased risk of certain injuries associated with air bag deployment, especially the risks to small occupants, often women. These injuries include serious eye and upper extremity injuries and even fatalities. This study investigates the interaction of a deploying air bag with cadaveric upper extremities in a typical driving posture; testing concentrates on female occupants. The goals of this investigation are to determine the risk of upper extremity injury caused by primary contact with a deploying air bag and to elucidate the mechanisms of these upper extremity injuries. Five air bags were used that are representative of a wide range of air bag ‘aggressivities’ in the current automobile fleet. This air bag ‘aggressivity’ was quantified using the response of a dummy forearm under air bag deployment.

This paper discusses the consumer and news media perceptions about air bags that had to be taken into account by the National Highway Traffic Safety Administration in making rulemaking decisions in 1997. Addressing these perceptions was a major concern as the agency made preparations to allow identifiable groups of people at risk from an air bag deployments to have on-off switches installed in their vehicles.

The protection of a vehicle occupant in a frontal crash is a combination of vehicle front structural design and occupant restraint design. Once chosen and manufactured, these design features must interact with a wide variety of structural characteristics in potential crash partners. If robust, the restraint design will provide a high level of protection for a wide variety of crash conditions. This paper examines how robust a given restraint system is for occupant self-protection and how frontal design can improve the restraint performance of potential crash partners, thus improving their restraint robustness as well. To examine restraint robustness in self protection, the effect of various vehicle deceleration characteristics on occupant injury potential is investigated for a given restraint design. A MADYMO model of a 1996 Taurus interior and its restraint system with a Hybrid III 50th percentile male dummy are simulated and subjected to 650 crash pulses taken during 25 years of U.S.

In crashes between heavy trucks and light vehicles, most of the fatalities are the occupants of the light vehicle. A reduction in heavy truck stopping distance should lead to a reduction in the number of crashes, the severity of crashes, and consequently the numbers of fatalities and injuries. This study made use of the National Advanced Driving Simulator (NADS). NADS is a full immersion driving simulator used to study driver behavior as well as driver-vehicle reactions and responses. The vehicle dynamics model of the existing heavy truck on NADS had been modified with the creation of two additional brake models. The first was a modified S-cam (larger drums and shoes) and the second was an air-actuated disc brake system. A sample of 108 CDL-licensed drivers was split evenly among the simulations using each of the three braking systems. The drivers were presented with four different emergency stopping situations.

Since 1994, the New Car Assessment Program (NCAP) of the National Highway Traffic Safety Administration (NHTSA) has compiled upper neck loads for the belt and air bag restrained 50th percentile male Hybrid III dummy. Over five years from 1994 to 1998, in frontal crash tests, NCAP collected upper neck data for 118 passenger cars and seventy-eight light trucks and vans. This paper examines these data and attempts to assess the potential for neck injury based on injury criteria included in FMVSS No. 208 (for the optional sled test). The paper examines the extent of serious neck injury in real world crashes as reported in the National Automotive Sampling System (NASS). The results suggest that serious neck injuries do occur at higher speeds for crashes involving occupants restrained by belts in passenger cars.

On-board Camera/Video Imaging Systems (C/VISs) for heavy vehicles display live images to the driver of selected areas to the sides, and in back of the truck's exterior using displays inside the truck cabin. They provide a countermeasure to blind-spot related crashes by allowing drivers to see objects not ordinarily visible by a typical mirror configuration, and to better judge the clearance between the trailer and an adjacent vehicle when changing lanes. The Virginia Tech Transportation Institute is currently investigating commercial motor vehicle (CMV) driver performance with C/VISs through a technology field demonstration sponsored by the National Highway Traffic Safety Administration (NHTSA) and the Federal Motor Carrier Safety Administration (FMCSA). Data collection, which consists of recording twelve CMV drivers performing their daily employment duties with and without a C/VIS for four months, is currently underway.

This paper presents the details of the model for the physical steering system used on the National Advanced Driving Simulator. The system is basically a hardware-in-the-loop (steering feedback motor and controls) steering system coupled with the core vehicle dynamics of the simulator. The system's torque control uses cascaded position and velocity feedback and is controlled to provide steering feedback with variable stiffness and dynamic properties. The reference model, which calculates the desired value of the torque, is made of power steering torque, damping function torque, torque from tires, locking limit torque, and driver input torque. The model also provides a unique steering dead-band function that is important for on-center feel. A Simulink model of the hardware/software is presented and analysis of the simulator steering system is provided.

A research program was initiated to evaluate the performance of prototype dual stage passenger air bags in terms of both restraint system performance and deployment aggressivity for different size occupants. Variations in inflator partitions, vent hole diameter sizes, and deployment timing were examined. High speed unbelted sled tests were conducted with both 50th percentile male and 5th percentile female Hybrid III adult dummies at 48 kmph; and belted sled tests were conducted at 56 kmph. Low risk deployment tests with child dummies were conducted to evaluate air bag aggressivity. Overall, it was concluded that the dual stage air bag systems under evaluation had improved performance over the baseline single stage systems in terms of providing high speed protection while reducing aggressivity to out-of-position occupants; however, some dual stage systems may require additional occupant detection methodologies to suppress or control inflation.

The performance of air bags, as an occupant protection system, is of high interest to the National Highway Traffic Safety Administration (NHTSA or Agency). Since 1972, the NHTSA has operated a Special Crash Investigations (SCI) program which provides in-depth crash investigation data on new and rapidly changing occupant protection technologies in real-world crashes. The Agency uses these in-depth data to evaluate vehicle safety systems and form a basis for rulemaking actions. The data are also used by the automotive industry and other organizations to evaluate the performance of motor vehicle occupant protection systems such as air bags. This paper presents information from NHTSA's SCI program concerning crash investigations on air-bag-equipped vehicles. The paper focus is on data collection and some general findings in air bag crash investigations including: air-bag-related fatal and life-threatening injuries; side air bags; redesigned air bags and advanced air bags.