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Technical Paper

A Modeling Framework for Connectivity and Automation Co-simulation

2018-04-03
2018-01-0607
This paper presents a unified modeling environment to simulate vehicle driving and powertrain operations within the context of the surrounding environment, including interactions between vehicles and between vehicles and the road. The goal of this framework is to facilitate the analysis of the energy impacts of vehicle connectivity and automation, as well as the development of eco-driving algorithms. Connectivity and automation indeed provide the potential to use information about the environment and future driving to minimize energy consumption. To achieve this goal, the designers of eco-driving control strategies need to simulate a wide range of driving situations, including the interactions with other vehicles and the infrastructure in a closed-loop fashion.
Technical Paper

Advanced Automatic Transmission Model Validation Using Dynamometer Test Data

2014-04-01
2014-01-1778
As a result of increasingly stringent regulations and higher customer expectations, auto manufacturers have been considering numerous technology options to improve vehicle fuel economy. Transmissions have been shown to be one of the most cost-effective technologies for improving fuel economy. Over the past couple of years, transmissions have significantly evolved and impacted both performance and fuel efficiency. This study validates the shifting control of advanced automatic transmission technologies in vehicle systems by using Argonne National Laboratory's model-based vehicle simulation tool, Autonomie. Different midsize vehicles, including several with automatic transmission (6-speeds, 7-speeds, and 8-speeds), were tested at Argonne's Advanced Powertrain Research Facility (APRF). For the vehicles, a novel process was used to import test data.
Journal Article

Automated Model Initialization Using Test Data

2017-03-28
2017-01-1144
Building a vehicle model with sufficient accuracy for fuel economy analysis is a time-consuming process, even with the modern-day simulation tools. Obtaining the right kind of data for modeling a vehicle can itself be challenging, given that while OEMs advertise the power and torque capability of their engines, the efficiency data for the components or the control algorithms are not usually made available for independent verification. The U.S. Department of Energy (DOE) funds the testing of vehicles at Argonne National Laboratory, and the test data are publicly available. Argonne is also the premier DOE laboratory for the modeling and simulation of vehicles. By combining the resources and expertise with available data, a process has been created to automatically develop a model for any conventional vehicle that is tested at Argonne. This paper explains the process of analyzing the publicly available test data and computing the parameters of various components from the analysis.
Technical Paper

Autonomie Model Validation with Test Data for 2010 Toyota Prius

2012-04-16
2012-01-1040
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).
Technical Paper

Control Analysis and Model Validation for BMW i3 Range Extender

2017-03-28
2017-01-1152
The control analysis and model validation of a 2014 BMW i3-Range Extender (REX) was conducted based on the test data in this study. The vehicle testing was performed on a chassis dynamometer set within a thermal chamber at the Advanced Powertrain Research Facility at Argonne National Laboratory. The BMW i3-REX is a series-type plug-in hybrid range extended vehicle which consists of a 0.65L in-line 2-cylinder range-extending engine with a 26.6kW generator, 125kW permanent magnet synchronous AC motor, and 18.8kWh lithium-ion battery. Both component and vehicle model including thermal aspects, were developed based on the test data. For example, the engine fuel consumption rate, battery resistance, or cabin HVAC energy consumption are affected by the temperature. Second, the vehicle-level control strategy was analyzed at normal temperature conditions (22°C ambient temperature). The analysis focuses on the engine on/off strategy, battery SOC balancing, and engine operating conditions.
Journal Article

Control Analysis under Different Driving Conditions for Peugeot 3008 Hybrid 4

2014-04-01
2014-01-1818
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.
Technical Paper

Detailed Analysis of U.S. Department of Energy Engine Targets Compared To Existing Engine Technologies

2020-04-14
2020-01-0835
The U.S. Department of Energy, Vehicle Technologies Office (U.S. DOE-VTO) has been developing more energy-efficient and environmentally friendly highway transportation technologies that would enable the United States to burn less petroleum on the road. System simulation is an accepted approach to evaluate the fuel economy potential of advanced (future) technology targets. U.S. DOE-VTO defines the targets for advancement in powertrain technologies (e.g., engine efficiency targets, battery energy density, lightweighting, etc.) Vehicle system simulation models based on these targets have been generated in Autonomie, to reflect the different EPA classifications of vehicles for different advanced timeframes as part of DOE Benefits and Scenario Analysis (BaSce). It is also important to evaluate the progress of these component technical targets compared to existing technologies available in the market.
Technical Paper

Development and Validation of the Ford Focus Battery Electric Vehicle Model

2014-04-01
2014-01-1809
This paper presents the vehicle model development and validation process for the Ford Focus battery electric vehicles (BEVs) using Autonomie and test results from Advanced Powertrain Research Facility in Argonne National Laboratory. The parameters or characteristic values for the important components such as the electric machine and battery pack system are estimated through analyzing the test data of the multi cycle test (MCT) procedure under the standard ambient condition. A novel process was used to import vehicle test data into Autonomie. Through this process, a complete vehicle model of the Ford Focus BEV is developed and validated under ambient temperature for different drive cycles (UDDS, HWFET, US06 and Steady-State). The simulation results of the developed vehicle model show coincident results with the test data within 0.5% ∼ 4% discrepancies for electrical consumption.
Technical Paper

Fuel Efficient Speed Optimization for Real-World Highway Cruising

2018-04-03
2018-01-0589
This paper introduces an eco-driving highway cruising algorithm based on optimal control theory that is applied to a conventionally-powered connected and automated vehicle. Thanks to connectivity to the cloud and/or to infrastructure, speed limit and slope along the future route can be known with accuracy. This can in turn be used to compute the control variable trajectory that will minimize energy consumption without significantly impacting travel time. Automated driving is necessary to the implementation of this concept, because the chosen control variables (e.g., torque and gear) impact vehicle speed. An optimal control problem is built up where quadratic models are used for the powertrain. The optimization is solved by applying Pontryagin’s minimum principle, which reduces the problem to the minimization of a cost function with parameters called co-states.
Technical Paper

Honda Insight Validation Using PSAT

2001-08-20
2001-01-2538
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.
Technical Paper

Impact of Connectivity and Automation on Vehicle Energy Use

2016-04-05
2016-01-0152
Connectivity and automation are increasingly being developed for cars and trucks, aiming to provide better safety and better driving experience. As these technologies mature and reach higher adoption rates, they will also have an impact on the energy consumption: Connected and Automated Vehicles (CAVs) may drive more smoothly, stop less often, and move at faster speeds, thanks to overall improvements to traffic flows. These potential impacts are not well studied, and any existing studies tend to focus solely on conventional engine-powered cars, leaving aside electrified vehicles such as Hybrid Electric Vehicles (HEVs) and Battery Electric Vehicles (BEVs). This work intends to address this issue by analyzing the energy impact of various CAV scenarios on different types of electric vehicles using high-fidelity models. The vehicles-all midsize, one HEV, one BEV, and a conventional-are modeled in Autonomie, a high-fidelity, forward-looking vehicle simulation tool.
Technical Paper

Instantaneously Optimized Controller for a Multimode Hybrid Electric Vehicle

2010-04-12
2010-01-0816
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.
Technical Paper

Integration of a Modal Energy and Emissions Model into a PNGV Vehicle Simulation Model, PSAT

2001-03-05
2001-01-0954
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.
Technical Paper

Model-Based Systems Engineering and Control System Development via Virtual Hardware-in-the-Loop Simulation

2010-10-19
2010-01-2325
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.
Technical Paper

Modeling the Hybridization of a Class 8 Line-Haul Truck

2010-10-05
2010-01-1931
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.
Technical Paper

Plug-and-Play Software Architecture to Support Automated Model-Based Control Process

2010-10-05
2010-01-1996
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.
Technical Paper

Tahoe HEV Model Development in PSAT

2009-04-20
2009-01-1307
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.
Technical Paper

The New PNGV System Analysis Toolkit PSAT V4.1 - Evolution and Improvement

2001-08-20
2001-01-2536
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.
Technical Paper

Thermal Model Development and Validation for 2010 Toyota Prius

2014-04-01
2014-01-1784
This paper introduces control strategy analysis and performance degradation for the 2010 Toyota Prius under different thermal conditions. The goal was to understand, in as much detail as possible, the impact of thermal conditions on component and vehicle performances by analyzing a number of test data obtained under different thermal conditions in the Advanced Powertrain Research Facility (APRF) at Argonne National Laboratory. A previous study analyzed the control behavior and performance under a normal ambient temperature; thus the first step in this study was to focus on the impact when the ambient temperature is cold or hot. Based on the analyzed results, thermal component models were developed in which the vehicle controller in the simulation was designed to mimic the control behavior when temperatures of the components are cold or hot. Further, the performance degradation of the components was applied to the mathematical models based on analysis of the test data.
Technical Paper

Using Modeling and Simulation to Support Future Medium and Heavy Duty Regulations

2011-01-19
2011-26-0048
Other than in Japan, medium and heavy duty vehicles (MHDVs) are not regulated despite accounting for a significant portion of the fuel consumed (about 26% in the US in 2008). Government agencies worldwide are currently evaluating options to address that issue. Due to the large number of vehicle applications, some of them being “one of a kind”, vehicle modelling and simulation offers an attractive solution to medium and heavy duty regulations. This paper discusses the advantages and challenges of vehicle simulation to support regulations.
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