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This paper includes analysis results for the control strategy of the Peugeot 3008 Hybrid4, a diesel-electric hybrid vehicle, under different thermal conditions. The analysis was based on testing results obtained under the different thermal conditions in the Advanced Powertrain Research Facility (APRF) at Argonne National Laboratory (ANL). The objectives were to determine the principal concepts of the control strategy for the vehicle at a supervisory level, and to understand the overall system behavior based on the concepts. Control principles for complex systems are generally designed to maximize the performance, and it is a serious challenge to determine these principles without detailed information about the systems. By analyzing the test results obtained in various driving conditions with the Peugeot 3008 Hybrid4, we tried to figure out the supervisory control strategy.

Manufacturers have been considering various technology options to improve vehicle fuel economy. Some of the most promising technologies are related to vehicle electrification. To evaluate the benefits of vehicle electrification to support the 2017-2025 CAFE regulations, a study was conducted to simulate many of the most common electric drive powertrains currently available on the market: 12V Micro Hybrid Vehicle (start/stop systems), Belt-integrated starter generator (BISG), Crank-integrated starter generator (CISG), Full Hybrid Electric Vehicle (HEV), PHEV with 20-mile all-electric range (AER) (PHEV20), PHEV with 40-mile AER (PHEV40), Fuel-cell HEV and Battery Electric vehicle with 100-mile AER (EV100). Different vehicle classes were also analyzed in the study process: Compact, Midsize, Small SUV, Midsize SUV and Pickup. This paper will show the fuel displacement benefit of each powertrain across vehicle classes.

Plug-in Hybrid Electric Vehicles (PHEVs) have demonstrated the potential to provide significant reduction in fuel use across a wide range of dynamometer test driving cycles. Companies and research organizations are involved in numerous research activities related to PHEVs. One of the current unknowns is the impact of driving behavior and standard test procedure on the true benefits of PHEVs from a worldwide perspective. To address this issue, five different PHEV powertrain configurations (input split, parallel, series, series-output split and series-parallel), implemented on vehicles with different all-electric ranges (AERs), were analyzed on three different standard cycles (i.e., Urban Dynamometer Driving Schedule, Highway Fuel Economy Test, and New European Driving Cycle). Component sizes, manufacturing cost, and fuel consumption were analyzed for a midsize car in model year 2020 through the use of vehicle system simulations.

The first commercially available Plug-In Hybrid Electric Vehicle (PHEV), the General Motors (GM) Volt, was introduced into the market in December 2010. The Volt's powertrain architecture provides four modes of operation, including two that are unique and maximize the Volt's efficiency and performance. The electric transaxle has been specially designed to enable patented operating modes both to improve the electric driving range when operating as a battery electric vehicle and to reduce fuel consumption when extending the range by operating with an internal combustion engine (ICE). However, details on the vehicle control strategy are not widely available because the supervisory control algorithm is proprietary. Since it is not possible to analyze the control without vehicle test data obtained from a well-designed Design-of-Experiment (DoE), a highly instrumented GM Volt, including thermal sensors, was tested at Argonne National Laboratory's Advanced Powertrain Research Facility (APRF).

Because Plug-in Hybrid Electric Vehicles (PHEVs) substitute electrical power from the utility grid for fuel, they have the potential to reduce petroleum use significantly. However, adoption of PHEVs has been hindered by expensive, low-energy batteries. Recent improvements in Li-ion batteries and hybrid control have addressed battery-related issues and have brought PHEVs within reach. The FreedomCAR Office of Vehicle Technology has a program that studies the potential benefit of PHEVs. This program also attempts to clarify and refine the requirements for PHEV components. Because the battery appears to be the main technical barrier, both from a performance and cost perspective, the main efforts have been focused on that component. Working with FreedomCAR energy storage and vehicle experts, Argonne National Laboratory (Argonne) researchers have developed a process to define the requirements of energy storage systems for plug-in applications.

The U.S. Department of Energy (DOE) has invested considerable research and development (R&D) effort into Plug-in Hybrid Electric Vehicle (PHEV) technology because of the potential fuel displacement offered by the technology. DOE's PHEV R&D Plan [1], which is driven by the desire to reduce dependence on foreign oil by diversifying the fuel sources of automobiles, describes the various activities required to achieve the goals. The U.S. DOE will use Argonne's Powertrain Systems Analysis Toolkit (PSAT) to guide its analysis activities, stating, “Argonne's Powertrain Systems Analysis Toolkit (PSAT) will be used to design and evaluate a series of PHEVs with various ‘primary electric’ ranges, considering all-electric and charge-depleting strategies.” PSAT was used to simulate three possible charge-depleting (CD) PHEV control strategies for a power split hybrid. Trip distance was factored into the CD strategies before the cycle was started.

Fuel cell vehicles are undergoing extensive research and development because of their potential for high efficiency and low emissions. Because fuel cell vehicles remain expensive and there is limited demand for hydrogen at present, very few fueling stations are being built. To try to accelerate the development of a hydrogen economy, some original equipment manufacturers in the automotive industry have been working on a hydrogen-fueled internal combustion engine (ICE) as an intermediate step. This paper compares the fuel economy potential of hydrogen powertrains to conventional gasoline vehicles. Several timeframes are considered: 2010, 2015, 2030, and 2045. To address the technology status uncertainty, a triangular distribution approach was implemented for each component technology. The fuel consumption and cost of five powertrain configurations will be discussed and compared with the conventional counterpart.

Plug-in Hybrid Electric Vehicles (PHEVs) use electric energy from the grid rather than fuel energy for most short trips, therefore drastically reducing fuel consumption. Different configurations can be used for PHEVs. In this study, the parallel pre-transmission, series, and power-split configurations were compared by using global optimization. The latter allows a fair comparison among different powertrains. Each vehicle was operated optimally to ensure that the results would not be biased by non-optimally tuned or designed controllers. All vehicles were sized to have a similar all-electric range (AER), performance, and towing capacity. Several driving cycles and distances were used. The advantages of each powertrain are discussed.

Argonne National Laboratory (Argonne) and Idaho National Laboratory (INL), working with the FreedomCAR and Fuels Partnership, lead activities in vehicle dynamometer and fleet testing as well as in modeling activities. By using Argonne’s Advanced Powertrain Research Facility (APRF), the General Motors (GM) Tahoe 2-mode was instrumented and tested in the 4-wheel-drive test facility. Measurements included both sensors and controller area network (CAN) messages. In this paper, we describe the vehicle instrumentation as well as the test results. On the basis of the analysis performed, we discuss the vehicle model developed in Argonne’s vehicle simulation tool, the Powertrain System Analysis Toolkit (PSAT), and its comparison with test data. Finally, on-road vehicle data, performed by INL, is discussed and compared with the dynamometer results.

Fuel cell vehicles are the subject of extensive research and development because of their potential for high efficiency and low emissions. Because fuel cell vehicles remain expensive and the demand for hydrogen is therefore limited, very few fueling stations are being built. To try to accelerate the development of a hydrogen economy, some original equipment manufacturers (OEM) in the automotive industry have been working on a hydrogen-fueled internal combustion engine (ICE) as an intermediate step. Despite its lower cost, the hydrogen-fueled ICE offers, for a similar amount of onboard hydrogen, a lower driving range because of its lower efficiency. This paper compares the fuel economy potential of hydrogen-fueled vehicles to their conventional gasoline counterparts. To take uncertainties into account, the current and future status of both technologies were considered.

A multimode transmission combines several power-split modes and possibly several fixed gear modes, thanks to complex arrangements of planetary gearsets, clutches and electric motors. Coupled to a battery, it can be used in a highly flexible hybrid configuration, which is especially practical for larger cars. The Chevrolet Tahoe Hybrid is the first light-duty vehicle featuring such a system. This paper introduces the use of a high-level vehicle controller based on instantaneous optimization to select the most appropriate mode for minimizing fuel consumption under a broad range of vehicle operating conditions. The control uses partial optimization: the engine ON/OFF and the battery power demand regulating the battery state-of-charge are decided by a rule-based logic; the transmission mode as well as the operating points are chosen by an instantaneous optimization module that aims at minimizing the fuel consumption at each time step.

To reduce development time and introduce technologies to the market more quickly, companies are increasingly turning to Model-Based Design. The development process - from requirements capture and design to testing and implementation - centers around a system model. Engineers are skipping over a generation of system design processes based on hand coding and instead are using graphical models to design, analyze, and implement the software that determines machine performance and behavior. This paper describes the process implemented in Autonomie, a plug-and-play software environment, to evaluate a component hardware in an emulated environment. We will discuss best practices and show the process through evaluation of an advanced high-energy battery pack within an emulated plug-in hybrid electric vehicle.

Hybrid electric vehicles have demonstrated their ability to significantly reduce fuel consumption for several medium- and heavy-duty applications. In this paper we analyze the impact on fuel economy of the hybridization of a tractor-trailer. The study is done in PSAT (Powertrain System Analysis Toolkit), which is a modeling and simulation toolkit for light- and heavy-duty vehicles developed by Argonne National Laboratory. Two hybrid configurations are taken into account, each one of them associated with a level of hybridization. The mild-hybrid truck is based on a parallel configuration with the electric machine in a starter-alternator position; this allows start/stop engine operations, a mild level of torque assist, and a limited amount of regenerative braking. The full-hybrid truck is based on a series-parallel configuration with two electric machines: one in a starter-alternator position and another one between the clutch and the gearbox.

Model-based control system design improves quality, shortens development time, lowers engineering cost, and reduces rework. Evaluating a control system's performance, functionality, and robustness in a simulation environment avoids the time and expense of developing hardware and software for each design iteration. Simulating the performance of a design can be straightforward (though sometimes tedious, depending on the complexity of the system being developed) with mathematical models for the hardware components of the system (plant models) and control algorithms for embedded controllers. This paper describes a software tool and a methodology that not only allows a complete system simulation to be performed early in the product design cycle, but also greatly facilitates the construction of the model by automatically connecting the components and subsystems that comprise it.

This paper describes the integration of a Modal Energy and Emissions Model (MEEM) into a hybrid-electric vehicle simulation model, the PNGV System Analytic Toolkits (PSAT). PSAT is a forward-looking computer simulation model for advanced-technology vehicles. MEEM is a vehicle fuel-consumption and emissions model developed by one of the authors for internal-combustion-engine (ICE) -powered vehicles. MEEM engine simulation module uses a power-demand physical model based on a parameterized analytical representation of engine fuel and emissions production. One major advantage of MEEM is that it does not rely on steady-state engine maps, which are usually not available for most production vehicles; rather, it depends on a list of engine parameters that are calibrated based on regular vehicle dynamometer testing. The integrated PSAT-MEEM model can be used effectively to predict fuel consumption and emissions of various ICE-powered vehicles with both conventional and hybrid power trains.

Hybrid electric vehicles (HEVs) combine two sources of energy and offer a wide variety of component and drivetrain configurations. However, optimizing the blending of these two energy sources is complex. Argonne National Laboratory (ANL) working with the Partnership for a New Generation of Vehicles (PNGV), maintains hybrid vehicle simulation software, the PNGV System Analysis Toolkit (PSAT). PSAT allows users to choose the best configuration and to optimize the control strategy in simulations. The importance of component models and the complexity involved in setting up optimized control laws require validation of the models and control strategies developed in PSAT. In this paper, we first describe our capability to validate each component model with an actual component test, using test stand facilities. Once each component model has been validated, ANL can perform tests on a whole HEV by using a chassis dynamometer.

Argonne National Laboratory (ANL), working with the Partnership for a New Generation of Vehicles (PNGV), maintains hybrid vehicle simulation software: the PNGV System Analysis Toolkit (PSAT). The importance of component models and the complexity involved in setting up optimized control strategies require validation of the models and controls developed in PSAT. Using ANL's Advanced Powertrain Test Facilities (APTF), more than 50 tests on the Honda Insight were used to validate the PSAT drivetrain configuration. Extensive instrumentation, including the half-shaft torque sensor, provides the data needed for through comparison of model results and test data. In this paper, we will first describe the process and the type of test used to validate the models. Then we will explain the tuning of the simulated vehicle control strategy, based on the analysis of the differences between test and simulation.

Argonne National Laboratory (ANL), working with the Partnership for a New Generation of Vehicles (PNGV), maintains hybrid vehicle simulation software, the PNGV System Analysis Toolkit (PSAT). PSAT, originally proprietary, has been used by both DOE and the “Big Three” as a modeling tool. The number of PSAT users has increased recently because 15 universities participating in the 2001 FutureTruck competition were given the software for their use. PSAT allows companies to look at new types of vehicles (hybrids) and choose the best configuration according to customer expectations within a minimum of time. PSAT, a forward-looking model, allows the user to simulate a large number of different configurations (conventional, series, parallel, and power split). PSAT is well suited for development of control strategies; by using accurate dynamics component models as its code, PSAT can be implemented directly and tested at the bench scale or in a vehicle.

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.

Many leading companies in the automotive industry have been putting tremendous amount of efforts into developing new designs and technologies to make their products more energy efficient. It is straightforward to evaluate the fuel economy benefit of an individual technology in specific systems and components. However, when multiple technologies are combined and integrated into a whole vehicle, estimating the impact without building and testing an actual vehicle becomes very complex, because the efficiency gains from individual components do not simply add up. In an early concept phase, a projection of fuel efficiency benefits from new technologies will be extremely useful; but in many cases, the outlook has to rely on engineer’s insight since it is impractical to run tests for all possible technology combinations.