For years the trend in the automotive industry has been toward more complex electronic control systems. The number of electronic control units (ECUs) in vehicles is ever increasing as is the complexity of communication networks among the ECUs. Increasing fuel economy standards and the increasing cost of fuel is driving hybridization and electrification of the automobile. Achieving superior fuel economy with a hybrid powertrain requires an effective and optimized control system. On the other hand, mathematical modeling and simulation tools have become extremely advanced and have turned simulation into a powerful design tool. The combination of increasing control system complexity and simulation technology has led to an industry wide trend toward model based control design. Rather than using models to analyze and validate real world testing data, simulation is now the primary tool used in the design process long before real world testing is possible. Modeling is used in every step from architecture selection to control system validation before on-road testing begins. The Hybrid Electric Vehicle Team (HEVT) of Virginia Tech is participating in the 2011-2014 EcoCAR 2 competition in which the team is tasked with re-engineering the powertrain of a GM donated vehicle. The primary goals of the competition are to reduce well to wheels (WTW) petroleum energy use (PEU) and reduce WTW greenhouse gas (GHG) and criteria emissions while maintaining performance, safety, and consumer acceptability. This paper will present systematic methodology for using model based design techniques for architecture selection, control system design, control strategy optimization, and controller validation to meet the goals of the competition. Simple energy management and efficiency analysis will form the primary basis of architecture selection. Using a novel method, a series-parallel powertrain architecture is selected. The control system architecture and requirements is defined using a systematic approach based around the interactions between control units. Vehicle communication networks are designed to facilitate efficient data flow. Software-in-the-loop (SIL) simulation with Mathworks Simulink is used to refine a control strategy to maximize fuel economy. Finally hardware-in-the-loop (HIL) testing on a dSPACE HIL simulator is demonstrated for performance improvements, as well as for safety critical controller validation. The end product of this design study is a control system that has reached a high level of parameter optimization and validation ready for on-road testing in a vehicle. / Master of Science

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2012-2014 EcoCAR 2: Plugging in to the Future Advanced Vehicle Technology Competition series organized by Argonne National Lab (ANL), and sponsored by General Motors Corporation (GM) and the U.S. Department of Energy (DOE). The goals of the competition are to reduce well-to-wheel (WTW) petroleum energy consumption (PEU), WTW greenhouse gas (GHG) and criteria emissions while maintaining vehicle performance, consumer acceptability and safety. Following the EcoCAR 2 Vehicle Development Process (VDP) of designing, building, and refining an advanced technology vehicle over the course of the three year competition using a 2013 Chevrolet Malibu donated by GM as a base vehicle, the selected powertrain is a Series-Parallel Plug-In Hybrid Electric Vehicle (PHEV) with P2 (between engine and transmission) and P4 (rear axle) motors, a lithium-ion battery pack, an internal combustion engine, and an automatic transmission. Development of a charge sustaining control strategy for this vehicle involves coordination of controls for each of the main powertrain components through a distributed control strategy. This distributed control strategy includes component controllers for each individual component and a single supervisory controller responsible for interpreting driver demand and determining component commands to meet the driver demand safely and efficiently. For example, the algorithm accounts for a variety of system operating points and will penalize or reward certain operating points for other conditions. These conditions include but are not limited to rewards for discharging the battery when the state of charge (SOC) is above the target value or penalties for operating points with excessive emissions. Development of diagnostics and remedial actions is an important part of controlling the powertrain safely. In order to validate the control strategy prior to in-vehicle operation, simulations are run against a plant model of the vehicle systems. This plant model can be run in both controller Software- and controller Hardware-In-the-Loop (SIL and HIL) simulations. This paper details the development of the controls for diagnostics, major selection algorithms, and execution of commands and its integration into the Series-Parallel PHEV through the supervisory controller. This paper also covers the plant model development and testing of the control algorithms using controller SIL and HIL methods. This paper details reasons for any changes to the control system, and describes improvements or tradeoffs that had to be made to the control system architecture for the vehicle to run reliably and meet its target specifications. Test results illustrate how changes to the plant model and control code properly affect operation of the control system in the actual vehicle. The VT Malibu is operational and projected to perform well at the final competition. / Master of Science