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The Georgia Tech EcoCAR 3 team’s selection of a parallel hybrid electric vehicle (HEV) architecture for the EcoCAR 3 competition is presented in detail, with a focus on the team’s modeling and simulation efforts and how they informed the team’s architecture selection and subsequent component decisions. EcoCAR 3, sponsored by the United States Department of Energy and General Motors, is the latest in a series of Advanced Vehicle Technology Competitions (AVTCs) and features 16 universities from the United States and Canada competing to transform the 2016 Chevrolet Camaro into a hybrid electric American performance vehicle. Team vehicles will be scored on performance, emissions, fuel economy, consumer acceptability, and more over the course of the four-year competition. During the first year, the Georgia Tech team considered numerous component combinations and HEV architectures, including series RWD and AWD, parallel, and power-split.

This paper presents a detailed design study and associated considerations supporting the development of high-performance plug-in hybrid electric vehicles (PHEVs). Due to increasingly strict governmental regulations and increased consumer demand, automotive manufacturers have been tasked with the reduction of fuel consumption and greenhouse gas (GHG) emissions. PHEV powertrains can provide a needed balance in terms of fuel economy and vehicle performance by exploiting regenerative braking, pure electric vehicle operation, engine load-point shifting, and power-enhancing hybrid traction modes. Thus, properly designed PHEV powertrains can reduce fuel consumption while increasing vehicle utility and performance.

This paper presents a forward-looking simulation (FLS) approach for the front wheel drive (FWD) General Motors Allison Hybrid System II (GM AHS-II). The supervisory control approach is based on a dynamic programming-informed Equivalent Cost Minimization Strategy (ECMS). The controller development uses backward-looking simulations (BLS), which execute quickly by neglecting component transients while assuming exact adherence to a specified drive cycle. Since ECMS sometimes prescribes control strategies with rapid component transients, its efficacy remains unknown until these transients are modeled. This is addressed by porting the ECMS controller to a forward-looking simulation where component transients are modeled in high fidelity. Techniques of implementing the ECMS controller and commanding the various power plants in the GM AHS-II for FLS are discussed.

Turboelectric propulsion is a technology that can potentially reduce aircraft noise, increase fuel efficiency, and decrease harmful emissions. In a turbo-electric system, the propulsor (fans) is no longer connected to the turbine through a mechanical connection. Instead, a superconducting generator connected to a gas turbine produces electrical power which is delivered to distributed fans. This configuration can potentially decrease fuel burn by 10% [1]. One of the primary challenges in implementing turboelectric electric propulsion is designing the power distribution system to transmit power from the generator to the fans. The power distribution system is required to transmit 40 MW of power from the generator to the electrical loads on the aircraft. A conventional aircraft distribution cannot efficiently or reliably transmit this large amount of power; therefore, new power distribution technologies must be considered.

Power-split hybrid-electric vehicles (HEVs) employ two power paths between the internal combustion (IC) engine and the driven wheels routed through gearing and electric machines (EMs) composing an electrically variable transmission (EVT). The EVT allows IC engine control such that rotational speed can be independent of vehicle speed at all times. By breaking the rigid mechanical connection between the IC engine and the driven wheels, the EVT allows the IC engine to operate in the most efficient region of its characteristic brake specific fuel consumption (BSFC) map. If the most efficient IC engine operating point produces more power than is requested by the driver, the excess IC engine power can be stored in the energy storage system (ESS) and used later. Conversely, if the most efficient IC engine operating point does not meet the power request of the driver, the ESS delivers the difference to the wheels through the EMs.

A plug-in hybrid electric vehicle (PHEV) design with design parameters electric motor size, engine size, battery capacity, and battery chemistry type, is optimized with minimum cost as a measure of merit. The PHEV is required to meet a fixed set of performance constraints consisting of 0-60 mph acceleration, 50-70 mph acceleration, 0-30 mph acceleration in all electric operation, top speed, grade ability, and all electric range. The optimization is carried out for values of all electric range of 10, 20, and 40 miles. The social and economic impacts of the optimum designs in terms of reduced gasoline consumption and carbon emissions reduction are calculated. Argonne National Laboratory's Powertrain Systems Analysis Toolkit is used to simulate the performance and fuel economy of the PHEV designs. The costs of different PHEV components and the present value of battery replacements over the vehicle's life are used to determine the design's drivetrain cost.

The Georgia Tech FutureTruck Team has designed a strong parallel split-hybrid powertrain for the model year 2002 Ford Explorer SUV. The modified powertrain uses a Lincoln LS 3.0L, V-6, DOHC, aluminum engine driving the rear axle. An AC-150 from AC Propulsion is coupled to the front wheels through a 3.75:1 Auburn Gear speed reducer. This split-hybrid structure fits well into the Explorer and is to manufacture. The interior cabin has been maintained in a stock configuration by carefully integrating the added instrumentation and electric drive controls into the dash and console. The toque-blending hybrid electric control is designed to be charge sustaining such that the refueling procedures match those of the stock vehicle. When fully operational, this powertrain is expected to yield a net 25% increase in fuel efficiency while lowering emissions without any sacrifice in customer acceptability.

A hybrid electric vehicle (HEV) simulation has been developed for an electric-assist parallel configuration vehicle, at the University of Tennessee, Knoxville. The model was developed in MATLAB/SIMULINK using ADVISOR, a HEV simulation model developed by the National Renewable Energy Laboratory. The Neon simulation model implements a power control strategy using throttle position as the primary input. It incorporates other features of HEV power control such as battery regeneration and regenerative braking. A practical way of battery modeling is incorporated into this model. The model also simulates the vehicle operation as a pure electric vehicle (EV) or as a conventional vehicle (heat engine only). By using the Neon model, the performance of the vehicle has been analyzed using parametric analysis of the vehicle components and power control parameters. Recommendations are given for improving the design based on the simulation results.

Neural network augmented model inversion control is used to provide a civilian tilt-rotor aircraft with consistent response characteristics throughout its operating envelope, including conversion flight. The implemented response types are Attitude Command Attitude Hold in the longitudinal channel, and Rate Command Attitude Hold about the roll and yaw axes. This article describes the augmentation in the roll channel and the augmentation for the yaw motion including Heading Hold at low airspeeds and automatic Turn Coordination at cruise flight. Conventional methods require extensive gain scheduling with tilt-rotor nacelle angle and airspeed. A control architecture is developed that can alleviate this requirement and thus has the potential to reduce development time. It also facilitates the implementation of desired handling qualities, and permits compensation for partial failures.

A technique is proposed for examining complex behaviors in the “pilot - vehicle - operational conditions” system using an autonomous situational model of flight. The goal is to identify potentially critical flight situations in the system behavior early in the design process. An exhaustive set of flight scenarios can be constructed and modeled on a computer by the designer in accordance with test certification requirements or other inputs. Distinguishing features of the technique include the autonomy of experimentation (the pilot and a flight simulator are not involved) and easy planning and quick modeling of complex multi-factor flight cases. An example of mapping airworthiness requirements into formal scenarios is presented. Simulation results for various flight situations and aircraft types are also demonstrated.