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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.

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.

Proper electric and thermal management of an HEV battery pack, consisting of many modules of cells, is imperative. During operation, voltage and temperature differences in the modules/cells can lead to electrical imbalances from module to module and decrease pack performance by as much as 25%. An active battery management system (BMS) is a must to monitor, control, and balance the pack. The University of Toledo, with funding from the U.S. Department of Energy and in collaboration with DaimlerChrysler and the National Renewable Energy Laboratory has developed a modular battery management system for HEVs. This modular unit is a 2nd generation system, as compared to a previous 1st generation centralized system. This 2nd generation prototype can balance a battery pack based on cell-to-cell measurements and active equalization. The system was designed to work with several battery types, including lithium ion, NiMH, or lead acid.

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.

Hybrid electric vehicles, plug-in hybrid electric vehicles, and battery electric vehicles offer the potential to reduce both oil imports and greenhouse gases, as well as to offer a financial benefit to the driver. However, assessing these potential benefits is complicated by several factors, including the driving habits of the operator. We focus on driver aggression, i.e., the level of acceleration and velocity characteristic of travel, to (1) assess its variation within large, real-world drive datasets, (2) quantify its effect on both vehicle efficiency and economics for multiple vehicle types, (3) compare these results to those of standard drive cycles commonly used in the industry, and (4) create a representative drive cycle for future analyses where standard drive cycles are lacking.

Fuel cell hybrid vehicles (FCHVs) use an energy management strategy to partition the power supplied by the fuel cell and energy storage system (ESS). This paper presents an adaptive energy management strategy, created in the ADVISOR™ software, for a series FCHV. The strategy uses a local or “real-time” optimization approach, which aims to reduce total energy consumption at each instantaneous time interval by dynamically adjusting the amount of power supplied by the fuel cell and ESS. Compared with a static control strategy, the adaptive strategy improved the simulated FCHV's fuel economy by 1.4%-8.5%, depending on the drive cycle.

The objective of the research into modeling and simulation was to provide an improvement to the Wayne State EcoCAR 2 team’s math-based modeling and simulation tools for hybrid electric vehicle powertrain analysis, with a goal of improving the simulation results to be less than 10% error to experimental data. The team used the modeling and simulation tools for evaluating different outcomes based on hybrid powertrain architecture changes (hardware), and controls code development and testing (software). The first step was model validation to experimental data, as the plant models had not yet been validated. This paper includes the results of the team’s work in the U.S. Department of Energy’s EcoCAR 2 Advanced vehicle Technical Competition for university student teams to create and test a plug-in hybrid electric vehicle for reducing petroleum oil consumption, pollutant emissions, and Green House Gas (GHG) emissions.

This paper determines the impact of ambient temperature on energy consumption of a variety of vehicles in the laboratory. Several conventional vehicles, several hybrid electric vehicles, a plug-in hybrid electric vehicle and a battery electric vehicle were tested for fuel and energy consumption under test cell conditions of 20°F, 72°F and 95°F with 850 W/m₂ of emulated radiant solar energy on the UDDS, HWFET and US06 drive cycles. At 20°F, the energy consumption increase compared to 72°F ranges from 2% to 100%. The largest increases in energy consumption occur during a cold start, when the powertrain losses are highest, but once the powertrains reach their operating temperatures, the energy consumption increases are decreased. At 95°F, the energy consumption increase ranges from 2% to 70%, and these increases are due to the extra energy required to run the air-conditioning system to maintain 72°F cabin temperatures.

Models for the components of a long-duration UAV power system are set forth. The models include the solar array, solar array power converter, fuel cell and electrolyzer system and corresponding power converter, and propulsion load. Based on these models, a power management control is derived, which when coupled with the component models, are used to simulate power system performance during start-up, through a day-night cycle, and through a solar eclipse.

The recovery of braking energy through regenerative braking is a key enabler for the improved efficiency of Hybrid Electric Vehicles, Plug-in Hybrid Electric, and Battery Electric Vehicles (HEV, PHEV, BEV). However, this energy is often treated in a simplified fashion, frequently using an overall regeneration efficiency term, ξrg [1], which is then applied to the total available braking energy of a given drive-cycle. In addition to the ability to recapture braking energy typically lost during vehicle deceleration, hybrid and plug-in hybrid vehicles also allow for reduced or zero engine fueling during vehicle decelerations. While regenerative braking is often discussed as an enabler for improved fuel economy, reduced fueling is also an important component of a hybrid vehicle's ability to improve overall fuel economy.

The 2001 FutureTruck competition involved 15 universities from across North America that were invited to apply a wide range of advanced technologies to improve energy efficiency and reduce greenhouse gas impact while producing near-zero regulated exhaust emissions in a 2000 Chevrolet Suburban. The modified vehicles designated as FutureTrucks demonstrated improvements in greenhouse gas emissions, tailpipe emissions, and over-the-road fuel economy compared with the stock vehicle on which they were based. The technologies represented in the vehicles included ICE-engines and fuel cell hybrid electric vehicle propulsion systems, a range of conventional and alternative fuels, advanced exhaust emissions controls, and light weighting technologies.

As part of an ongoing vehicle benchmarking effort at Argonne National Laboratory, four different power-split HEVs were tested on a chassis dynamometer to analyze their operational behavior and understand the control strategy and its relationship to the individual features of the vehicles tested. The controls that select the way in which engine operation matches best engine efficiency load points appears to have evolved From the Gen 1 to the Gen 2 Toyota Prius. The Ford Escape HEV and Lexus RX400h were also analyzed by using similar methods, although the data are not as extensive as those for the Prius hybrids. Whereas the Escape HEV appeared to operate in a manner similar to that of the Gen 1 Prius, the RX400h (with its relatively large engine) loads the engine with excess battery charge to keep it operating at higher power levels - apparently to improve overall efficiency.

The solid oxide fuel cell (SOFC) system has emerged as an important technology for automotive and stationary applications. Modeling and simulation of the SOFC system have been utilized as an integral tool in an accelerated joint SOFC system development program. Development of unique modeling approaches and their results are discussed and compared with experimental performance. One dimensional system level analysis using Aspen with an embedded stack electrochemical model was performed resulting in effective sub-system partitioning and requirements definition. Further, a three-dimensional integrated electrochemical / thermal / computational fluid dynamics analysis of steady-state operation was employed. The combination of one-dimensional and three-dimensional environments led to effective performance projection at all levels in the system, resulting in optimization of overall system performance early in the design cycle.

Developed by the U.S. Environmental Protection Agency (EPA), the Multi-scale mOtor Vehicle Emission Simulator (MOVES) is used to estimate inventories and projections through 2050 at the county or national level for energy consumption, nitrous oxide (N2O), and methane (CH4) from highway vehicles. To simulate a large number of vehicles and fleets on numerous driving cycles, EPA developed a binning technique characterizing the energy rate for varying Vehicle Specific Power (VSP) under predefined vehicle speed ranges. The methodology is based upon the assumption that the vehicle behaves the same way for a predefined vehicle speed and power demand. While this has been validated for conventional vehicles, it has not been for advanced vehicle powertrains, including hybrid electric vehicles (HEVs) where the engine can be ON or OFF depending upon the battery State-of-Charge (SOC).

This paper analyzes four recent major studies carried out by MIT, a GM-led team, Directed Technologies, Inc., and A. D. Little, Inc. to assess advanced technology vehicles. These analyses appear to differ greatly concerning their perception of the energy benefits of advanced technology vehicles, leading to great uncertainties in estimating full-fuel-cycle (or “well-to-wheel”) greenhouse gas (GHG) emission reduction potentials and/or fuel feedstock requirements per mile of service. Advanced vehicles include, but are not limited to, advanced gasoline and diesel internal combustion engine (ICE) vehicles, hybrid electric vehicles (HEVs) with gasoline, diesel, and compressed natural gas (CNG) ICEs, and various kinds of fuel-cell based vehicles (FCVs), such as direct hydrogen FCVs and gasoline or methanol fuel-based FCVs.

Hydrogen is widely considered a promising fuel for future transportation applications for both, internal combustion engines and fuel cells. Due to their advanced stage of development and immediate availability hydrogen combustion engines could act as a bridging technology towards a wide-spread hydrogen infrastructure. Although fuel cell vehicles are expected to surpass hydrogen combustion engine vehicles in terms of efficiency, the difference in efficiency might not be as significant as widely anticipated [1]. Hydrogen combustion engines have been shown capable of achieving efficiencies of up to 45 % [2]. One of the remaining challenges is the reduction of nitric oxide emissions while achieving peak engine efficiencies. This paper summarizes research work performed on a single-cylinder hydrogen direct injection engine at Argonne National Laboratory.

The Prius - a power-split hybrid electric vehicle from Toyota - has become synonymous with the word “Hybrid.” As of October 2010, two million of these vehicles had been sold worldwide, including one million vehicles purchased in the United States. In 2004, the second generation of the vehicle, the Prius MY04, enhanced the performance of the components with advanced technologies, such as a new magnetic array in the rotors. However, the third generation of the vehicle, the Prius MY10, features a remarkable change of the configuration - an additional reduction gear has been added between the motor and the output of the transmission [1]. In addition, a change in the energy management strategy has been found by analyzing the results of a number of tests performed at Argonne National Laboratory's Advanced Powertrain Research Facility (ARRF).

Süd-Chemie Inc. is producing and supplying an autothermal reforming (ATR) catalyst that was developed by Argonne National Laboratory (ANL) for reforming hydrocarbon fuels to generate H2 for automotive fuel cell systems. The catalyst is derived from solid oxide fuel cell technology, where a transition metal is supported on an oxide-ion-conducting substrate, such as ceria or zirconia, that is doped with an un-reducible oxide, such as gadolinium or samarium, to improve its oxide ion conductivity and to increase the number of surface oxygen ion vacancies. The catalyst has been shown to produce an H2-rich gas (reformate) from a wide variety of hydrocarbon fuels, including methane, natural gas, and commercial-grade gasolines and diesels with high selectivity. Platinum was the transition metal used in the first generation of the ANL catalyst.

Alternative electric motor geometry with potentially increased efficiency is being considered for hybrid electric vehicle applications. An axial flux motor with a dynamically adjustable air gap (i.e., mechanical field weakening) has been tested, analyzed, and modeled for use in a vehicle simulation tool at Argonne National Laboratory. The advantage of adjusting the flux is that the motor torque-speed characteristics can better match the vehicle load. The challenge in implementing an electric machine with these qualities is to develop a control strategy that takes advantage of the available efficiency improvements without using excessive energy to mechanically adjust the air gap and thus reduce the potential energy savings. Motor efficiency was mapped in terms of speed, torque, supply voltage, and rotor-to-stator air gap.

This study undertakes an investigation of the effect of battery charge balance in hybrid electric vehicles (HEVs) on EPA fuel economy label values. EPA's updated method was fully implemented in 2011 and uses equations which weight the contributions of fuel consumption results from multiple dynamometer tests to synthesize city and highway estimates that reflect average U.S. driving patterns. For the US06 and UDDS cycles, the test results used in the computation come from individual phases within the overall certification driving cycles. This methodology causes additional complexities for hybrid vehicles, because although they are required to be charge-balanced over the course of a full drive cycle, they may have net charge or discharge within the individual phases. As a result, the fuel consumption value used in the label value calculation can be skewed.