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This study evaluates powertrain technologies capable of reducing light duty vehicle fuel consumption for compliance with 2025 CAFE standards. A fully integrated GT-Power engine model with physics based sub-models was developed to capture any positive or negative synergies between the technologies. The two zone multi-cylinder engine model included typical thermodynamic subroutines, with predictive combustion, flame quench and knock models, along with map-based turbocharger models to capture key combustion and efficiency behaviors. The engine model was calibrated to data from a boosted GDI engine and exercised through one series of current and production viable technology configurations for 2025 regulations.

This study evaluates the fuel economy implication of powertrain technologies capable of reducing light duty vehicle fuel consumption for compliance with 2025 CAFE standards. In a companion paper, a fully integrated GT-Power engine model was used to evaluate the effectiveness of one plausible series of engine technologies, including valve train improvements such as dual cam phasing and discrete variable valve lift, and engine downsizing with turbocharging and cooled EGR. In this paper, those engine efficiency/performance results are used in a vehicle drive cycle simulation to estimate the impact of engine and transmission technology improvements on light duty vehicle fuel consumption/economy over the EPA’s FTP and HWY test schedules. The model test vehicle is a midsized sedan based on the MY2012 Ford Fusion.

The compressive behavior of lithium-iron phosphate battery cells is investigated by conducting in-plane constrained compression tests and out-of-plane compression tests of representative volume element (RVE) specimens. The results for cell RVE specimens under in-plane constrained compression tests without pre-strains and with pre-strains in the out-of-plane direction indicate that the load carrying capacity is characterized by the buckling of cell specimens. As the pre-strain increases, the nominal compressive stress-strain curve becomes higher. The nominal stress-strain curves in the out-of-plane direction were also obtained and used to determine the elastic moduli for the elastic buckling analyses of the cell components in the cell RVE specimens with different pre-strains. Based on the elastic buckling analyses for a beam with different lateral constraints due to different pre-strains in the out-of-plane direction, the number of half waves and the buckling stresses were obtained.

New vehicle control algorithms are needed to meet future emissions and fuel economy mandates that are quite likely to require a measurement of ambient specific humidity (SH). Current practice is to obtain the SH by measurement of relative humidity (RH), temperature and barometric pressure with physical sensors, and then to estimate the SH using a fit equation. In this paper a novel approach is described: a system of neural networks trained to estimate the SH using data that already exists on the vehicle bus. The neural network system, which is referred to as a virtual SH sensor, incorporates information from the global navigation satellite system such as longitude, latitude, time and date, and from the vehicle climate control system such as temperature and barometric pressure, and outputs an estimate of SH. The conclusion of this preliminary study is that neural networks have the potential of being used as a virtual sensor for estimating ambient and intake manifold's SH.

As lightweight materials and advanced combustion engines are being used in both conventional and electrified vehicles with diverse fuels, it is necessary to evaluate the individual and combined impact of these technologies to reduce energy and greenhouse gas (GHG) emissions. This work uses life cycle assessment (LCA) to evaluate the total energy and GHG emissions for baseline and lightweight internal combustion vehicles (ICVs), hybrid electric vehicles (HEVs) and plug-in hybrid electric vehicles (PHEVs) when they are operated with baseline and advanced gasoline and ethanol engines. Lightweight vehicle models are evaluated with primary body-in-white (BIW) mass reductions using aluminum and advanced/high strength steel (A/HSS) and secondary mass reductions that include powertrain re-sizing. Advanced engine/fuel strategies are included in the vehicle models with fuel economy maps developed from single cylinder engine models.

Automakers have the opportunity to utilize bio-based composite materials to lightweight cars while replacing conventional, nonrenewable resource materials. In this study, Life Cycle Assessment (LCA) is used to understand the potential benefits and tradeoffs associated with the implementation of bio-based composite materials in automotive component production. This cradle-to-grave approach quantifies the fiber and resin production as well as material processing, use, and end of life for both a conventional glass-reinforced polypropylene component as well as a cellulose-reinforced polypropylene component. The comparison is calculated for an exterior component on a high performance vehicle. The life cycle primary energy consumption and global warming potential (GWP) are evaluated. Reduced GWP associated with the alternative component are due to the use of biomass as process energy and carbon sequestration, in addition to the alternative material component's lightweighting effect.

This book provides a broad and comprehensive look at hybrid powertrain technologies for commercial vehicles. It begins with the fundamentals of hybrid powertrain systems, government regulations, and driving cycles, then provides design guidelines and key components of hybrid powertrains for commercial vehicles. It was written for vehicle and component engineers and developers, researchers, students, policymakers, and business executives in the commercial vehicle and transportation industries to help them understand the fundamentals of hybrid powertrain technologies and market requirements for commercial vehicles. It is useful for anyone who designs or is interested in hybrid powertrains and their key components. The term ‘commercial vehicle’ applies to everything from light delivery vehicles to class 8 long haul trucks, buses, and coaches. These vehicles are used for a wide range of duties, including transporting goods or people and infrastructure service.

An experimental study has been conducted to investigate the effects of indolene-ethanol blends on engine performance during homogeneous charge compression ignition (HCCI) operation of single-cylinder engine. The engine performance and HCCI stability were investigated and the high enthalpy of vaporization of ethanol resulted in significant intake charge cooling and limited the stable HCCI operation to higher intake temperatures. In the second part of the study, intake air preheat temperature was used to compensate for some of the thermal effects introduced by the fuel blends. The effects of equivalence ratio at a same end of compression temperature for different fuel blends showed that increasing the ethanol content of the fuel blend can extend the stable HCCI lean operating limit. Engine performance was characterized by in-cylinder pressure data, heat release rate, indicated mean effective pressure and exhaust gas emissions (NO and HC).

Software usability is a quality attribute defined as ?the extent to which a product can be used by specified users to achieve specified goals with effectiveness, efficiency and satisfaction in a specific context of use? (ISO 9241, 1998), usability is also referred to as ?quality in use? (ISO 14598, 1999). Presenter Anabell Beltran, Stoneridge Electronics North America

The paper describes the approach, addresses integration challenges and discusses capabilities of the Hybrid Powertrain-in-the-Loop (H-PIL) facility for the series/hydrostatic hydraulic hybrid system. We describe the simulation of the open-loop and closed-loop hydraulic hybrid systems in H-PIL and its use for concurrent engineering and development of advanced supervisory strategies. Presenter Fernando Tavares, Univ. of Michigan

Electrification and hybridization show great potential for improving fuel economy and reducing emission in heavy-duty vehicles. However, high battery cost is unavoidable due to the requirement for large batteries capable of providing high electric power for propulsion. The battery size and cost can be reduced with advanced battery control strategies ensuring safe and robust operation covering infrequent extreme conditions. In this paper, the impact of such a battery control strategy on battery sizing and fuel economy is investigated under various military and heavy-duty driving cycles. The control strategy uses estimated Li-ion concentration information in the electrodes to prevent battery over-charging and over-discharging under aggressive driving conditions. Excessive battery operation is moderated by adjusting allowable battery power limits through the feedback of electrode-averaged Li-ion concentration estimated by an extended Kalman filter (EKF).

The paper describes the approach, addresses integration challenges and discusses capabilities of the Hybrid Powertrain-in-the-Loop (H-PIL) facility for the series/hydrostatic hydraulic hybrid system. We describe the simulation of the open-loop and closed-loop hydraulic hybrid systems in H-PIL and its use for concurrent engineering and development of advanced supervisory strategies. The configuration of the hydraulic-hybrid system and details of the hydraulic circuit developed for the H-PIL integration are presented. Next, software and hardware interfaces between the real components and virtual systems are developed, and special attention is given to linking component-level controllers and system-level supervisory control. The H-PIL setup allows imposing realistic dynamic loads on hydraulic pump/motors and accumulator based on vehicle driving schedule.

A supervisory controller strategy for a hybrid vehicle coordinates the operation of the two power sources onboard of a vehicle to maximize objectives like fuel economy. In the past, various control strategies have been developed using heuristics as well as optimal control theory. The Stochastic Dynamic Programming (SDP) has been previously applied to determine implementable optimal control policies for discrete time dynamic systems whose states evolve according to given transition probabilities. However, the approach is constrained by the curse of dimensionality, i.e. an exponential increase in computational effort with increase in system state space, faced by dynamic programming based algorithms. This paper proposes a novel approach capable of overcoming the curse of dimensionality and solving policy optimization for a system with very large design state space.

This paper investigates series plug-in hybrid electric vehicle (PHEV) behavior during one-day with synthesized representative one-day missions. The amounts of electric energy and fuel consumption are predicted to assess the PHEV impact on the grid with respect to the driving distance and different charging scenarios: (1) charging overnight, (2) charging whenever possible. The representative cycles are synthesized using the extracted information from the real-world driving data in Southeast Michigan gathered through the Field Operational Tests (FOT) conducted by the University of Michigan Transportation Research Institute (UMTRI). The real-world driving data include 4,409 trips covering 830 independent days and temporal distributions of departure and arrival times. The sample size is large enough to represent real-world driving.

Rechargeable energy storage systems with Lithium-ion pouch cells are subject to various ambient temperature conditions and go through thousands of charge-discharge cycles during the life time of operation. The cells may change their thickness with internal heat generation, cycling and any other mechanisms. The stacked prismatic cells thus experience face pressure and this could impact the pack electrical performance. The pack consists of stiff end plates keeping the pack in tact using bolts, cooling fins to maintain cell temperature and foam padding in between cells. The pack level thermal requirements limit the amount of temperature increase during normal operating conditions. Similarly, the structural requirements state that the stresses and the deflection in the end plates should be minimal. Uncertainties in cell, foam mechanical and thermal properties might add variation to the pack performance.

Energy security and climate change challenges provide a strong impetus for investigating Electric Vehicle (EV) concepts. EVs link two major infrastructures, the transportation and the electric power grid. This provides a chance to bring other sources of energy into transportation, displace petroleum and, with the right mix of power generation sources, reduce CO₂ emissions. The main obstacles for introducing a large numbers of EVs are cost, battery weight, and vehicle range. Battery health is also a factor, both directly and indirectly, by introducing limits on depth of discharge. This paper considers a low-cost path for extending the range of a small urban EV by integrating a parallel hydraulic system for harvesting and reusing braking energy. The idea behind the concept is to avoid replacement of lead-acid or small Li-Ion batteries with a very expensive Li-Ion pack, and instead use a low-cost hydraulic system to achieve comparable range improvements.

Homogeneous charge compression ignition (HCCI) has received much attention in recent years due to its ability to reduce both fuel consumption and NO emissions compared to normal spark-ignited (SI) combustion. However, due to the limited operating range of HCCI, production feasible engines will need to employ a combination of combustion strategies, such as stoichiometric SI combustion at high loads and leaner burn spark-assisted compression ignition (SACI) and HCCI at intermediate and low loads. The goal of this study was to extend the high load limit of HCCI into the SACI region while maintaining a stoichiometric equivalence ratio. Experiments were conducted on a single-cylinder research engine with fully flexible valve actuation. In-cylinder pressure rise rates and combustion stability were controlled using cooled external EGR, spark assist, and negative valve overlap. Several engine loads within the SACI regime were investigated.

An oil-lubricated wet clutch has a direct impact on the drivability and fuel economy of a vehicle equipped with an automatic transmission system. However, a reliable analysis of clutch behavior still remains a challenge. The purpose of this study is to advance the state-of the-art in CFD methodology for modeling transient clutch behavior. First, a new iterative scheme is developed, in combination with commercial CFD software, which is capable of simulating the squeeze film process in a wet clutch. The numerical results are then validated using analytical solutions of the Reynolds equation for simplified clutch geometry and various boundary conditions. It is found that the choice of boundary conditions has a strong influence on squeeze film simulation. The iterative scheme is further validated by comparison to clutch engagement experiments.

Advances in robot performance have been limited by a lack of significant new advances in the mature field of battery technology. The limitations of batteries and other traditional energy sources have been recognized in other industries, and while much research has gone into alternatives or augmentation of energy sources through a hybridization scheme, very little of this research has been applied to robotic power systems. There are many potential advantages that could be obtained by shifting the focus of robotic power systems from the use of a single energy storage device to the inclusion of multiple storage/generation devices optimized for a robotic platform. The challenge lies in the development of the hardware and control algorithms for a scalable power delivery architecture which satisfies both the power and energy requirements of most unmanned ground vehicles.

The number of control actuators available on spark-ignition engines is rapidly increasing to meet demand for improved fuel economy and reduced exhaust emissions. The added complexity greatly complicates control strategy development because there can be a wide range of potential actuator settings at each engine operating condition, and map-based actuator calibration becomes challenging as the number of control degrees of freedom expand significantly. Many engine actuators, such as variable valve actuation and flow control valves, directly influence in-cylinder combustion through changes in gas exchange, mixture preparation, and charge motion. The addition of these types of actuators makes it difficult to predict the influences of individual actuator positioning on in-cylinder combustion without substantial experimental complexity.