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Technical Paper

Microsimulation-Based Evaluation of an Eco-Approach Strategy for Automated Vehicles Using Vehicle-in-the-Loop

2021-04-06
2021-01-0112
Connected and automated technologies poised to change the way vehicles operate are starting to enter the mainstream market. Methods to accurately evaluate these technologies, in particular for their impact on safety and energy, are complex due to the influence of static and environmental factors, such as road environment and traffic scenarios. Therefore, it is important to develop modeling and testing frameworks that can support the development of complex vehicle functionalities in a realistic environment. Microscopic traffic simulations have been increasingly used to assess the performance of connected and automated vehicle technologies in traffic networks. In this paper, we propose and apply an evaluation method based on a combination of microscopic traffic simulation (AIMSUN) and a chassis dynamometer-based vehicle-in-the-loop environment, developed at Argonne National Laboratory.
Technical Paper

Controls Development and Vehicle Refinement for a 99% Showroom Ready Parallel Through the Road Plug-In Hybrid Electric

2014-10-13
2014-01-2906
This paper details the control system development process for the University of Washington (UW) EcoCAR 2 team over the three years of the competition. Particular emphasis is placed upon the control system development and validation process executed during Year 3 of the competition in an effort to meet Vehicle Technical Specifications (VTS) established and refined by the team. The EcoCAR 2 competition challenges 15 universities across North America to reduce the environmental impact of a 2013 Chevrolet Malibu without compromising consumer acceptability. The project takes place over a three year design cycle, where teams select a hybrid architecture and fuel choice before defining a set of VTS goals for the vehicle. These VTS are selected based on the desired static and dynamic performance targets to balance fuel consumption and emissions with consumer acceptability requirements.
Technical Paper

Structuring a Hybrid Vehicle Supervisory Control System Simulink Model for Simpler Version Control with Multiple Software Developers

2014-04-01
2014-01-1923
This paper details the development process and model architecture used in the University of Washington's EcoCAR 2 hybrid supervisory controller. The EcoCAR 2 project challenges 15 universities across North America to create a hybrid vehicle that most effectively minimizes emissions and fuel consumption while still maintaining consumer acceptability. The supervisory controller for the University of Washington was designed to distribute torque to the various electric and combustion drive systems on a parallel though the road plug-in hybrid electric vehicle using Simulink and Stateflow. The graphical interface of Simulink offers some distinct advantages over text-based programming languages. However, there are also significant challenges posed by the software, particularly when several controls engineers are working in parallel on a large model with some type of version control.
Technical Paper

The Importance of Maximizing Grid Electricity Usage in the Component Selection and Design of a Midsize PHEV

2013-04-08
2013-01-0548
The University of Washington EcoCAR2 team (UWEC2) is currently in the process of building a Plug-in Hybrid Electric Vehicle (PHEV) for the EcoCAR2 Challenge. This competition challenges 15 universities across North America to reduce the environmental impact of a 2013 Chevrolet Malibu without compromising consumer acceptability. In order to be competitive in EcoCAR2, grid electricity is relied on heavily and the use of the Utility Factor method presented in SAE J2841 - Utility Factor Definitions must be used to compare emissions and consumption results with traditional vehicle results. Powertrain simulation in Autonomie was performed to explore many different hybrid architectures. The simulation results were normalized using the Utility Factor method to reach final architecture and component decisions.
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