A key element of General Motors' Advanced Propulsion Technology Strategy is the electrification of the automobile. The objectives of this strategy are reduced fuel consumption, reduced emissions and increased energy security/diversification.The introduction of hybrid vehicles was one of the first steps as a result of this strategy. To determine future opportunities and direction, an extensive study was completed to better understand the ability of Plug-in Hybrid Electric Vehicles (PHEV) and Extended-Range Electric Vehicles (E-REV) to address societal challenges. The study evaluated real world representative driving datasets to understand actual vehicle usage.Vehicle simulations were conducted to evaluate the merits of PHEV and E-REV configurations.As derivatives of conventional full hybrids, PHEVs have the potential to deliver a significant reduction in petroleum usage.However, the fuel consumption benefits are limited by the underlying constraints of the base hybrid systems and vehicles.Even with incremental electric power and speed improvements, the PHEV's lack of full-performance, all-electric capability requires engine operation under everyday speed and/or load conditions, regardless of available battery energy. This creates emissions concerns and can severely limit the actual all-electric driving range in the real world.The E-REV is principally an Electric Vehicle (EV) with full vehicle performance available as an EV. Significantly, it overcomes the historical EV re-charge time limitations by adding a fuel-powered electric generator to extend driving range. Actual all-electric driving can regularly be experienced throughout the working energy range of the vehicle's battery without fear of being stranded. The E-REV offers the opportunity for petroleum independence, and a dramatic reduction in emissions for many drivers.An E-REV traction drive and battery system needs to be specifically designed for the task. The systems are significantly more capable and larger than those designed for PHEVs. An E-REV is typically also architected to accommodate packaging of these systems while retaining performance and utility. The compelling benefits of the E-REV drive GM to address these challenges.The study results indicate that both the PHEVs and the E-REVs can play a role in addressing future needs. The study shows that in the real world the PHEV is quite likely to run with blended operation, but the E-REV is very likely to remain in EV mode for most drivers.GM is currently developing both PHEV and E-REV vehicles. The Saturn VUE Green Line PHEV is being developed as a derivative of the conventional 2-Mode Hybrid.The Chevrolet Volt E-REV is also under development with full performance, all-electric capability, but without practical range limitations. General Motors Corporation

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SUMMARYWhen a hybrid electric vehicle (HEV) is certified for emissions and fuel economy, its power management system must be charge sustaining over the drive cycle, meaning that the battery state of charge (SOC) must be at least as high at the end of the test as it was at the beginning of the test. During the test cycle, the power management system is free to vary the battery SOC so as to minimize a weighted combination of fuel consumption and exhaust emissions. This paper argues that shortest path stochastic dynamic programming (SP-SDP) offers a more natural formulation of the optimal control problem associated with the design of the power management system because it allows deviations of battery SOC from a desired setpoint to be penalized only at key off. This method is illustrated on a parallel hybrid electric truck model that had previously been analyzed using infinite-horizon stochastic dynamic programming with discounted future cost. Both formulations of the optimization problem yield a time-invariant causal state-feedback controller that can be directly implemented on the vehicle. The advantages of the shortest path formulation include that a single tuning parameter is needed to trade off fuel economy and emissions versus battery SOC deviation, as compared with two parameters in the discounted, infinite-horizon case, and for the same level of complexity as a discounted future-cost controller, the shortest-path controller demonstrates better fuel and emission minimization while also achieving better SOC control when the vehicle is turned off. Linear programming is used to solve both stochastic dynamic programs.

Control strategies have been developed for hybrid electric vehicles (HEV) that minimize fuel consumption while satisfying a charge sustaining constraint. Since one of the components of an HEV is typically the ubiquitous internal combustion engine, tailpipe emissions must also be considered. This paper uses shortest-path stochastic dynamic programming (SP-SDP) to address the minimization of a weighted sum of fuel consumption and tailpipe emissions for an HEV equipped with a dual mode electrically variable transmission (EVT) and a catalytic converter. The shortest path formulation of SDP is chosen to directly address the charge sustaining requirement. Using simple methods, an SP-SDP solution required more than eight thousand hours. Using linear programming and duality, an SP-SDP problem is solved in about three hours on a desktop PC. The resulting time-invariant feedback controller reduces tailpipe emissions by more than 50% when compared to a popular baseline controller.Index Terms-Dynamic programming, fuel economy, hybrid electric vehicle, powertrain control.