As the interest for electrified vehicles increases due to a conversion from a fleet of vehicles powered by fossil fuels to more environment friendly and climate neutral options it is important to investigate the different alternatives closely. This thesis analyzes one of the options on a micro level. Data have been collected from a Mitsubishi Outlander plug-in hybrid, including travelled distance, battery state of charge and outdoor temperature. The objective is to develop a model describing how these different factors affect the charging profile. Two models have been developed: one focusing on the total charging time and one for the total electrical charge transferred from the charging station. The analysis show for instance that at higher outside temperatures the charging time decreases but the total charge transferred increases. The final multidimensional models are created by separately looking at one variable at a time to see how it affects the total outcome.

In order to replace diesel energy in the transportation sector as well as to reduce the emission of green house gases (GHGs) and avoid air pollution for a sustainable future, electrification of vehicles is one of the most popular topics today. Plug-in hybrid electric vehicle (PHEV) technology is a promising technology for electrification of automobiles. It uses both internal combustion engine and electric motor for propulsion. The battery pack that propels the electric machine can be recharged from grid electricity and from kinetic energy converted from regenerative braking. In this thesis, field test data from a Volvo V70 prototype in a 2010 study by Volvo and Vattenfall (ETC, Volvo, Vattenfall, 2010) was analyzed with Matlab to give a better understanding of the usage of PHEVs and the performance of lithium-ion battery. Several conclusions were obtained in this thesis from the analyzed data. It was found that average and maximum driving speed in Diesel Mode is faster than that in Electric Mode. Different drivers had different preference of driving speed. Driving distance vary in different months; longer distance was running under Diesel Mode; A considerable number of 370 kg carbon dioxide emission was saved by using electric energy instead of diesel energy for the studied car during one year. Battery performance in cold temperature conditions needs to be considered and the vehicle was switched to Diesel Mode from Electric Mode when SOC falls below 30%.

This study analyzes how, in a possible electrification of the car fleet through plug-in hybrid electric vehicles (PHEV), the choice of objective function, which potentially reflects different stakeholders’ interests, may influence the resulting optimal PHEV battery range, the PHEV share in the vehicle fleet, the fleet total cost of ownership (TCO) savings, and the fleet electric drive fraction under various economic conditions and policy options. The optimal battery range can differ considerably among objective functions, especially between the objectives of maximizing the number of PHEVs and maximizing driving on electricity. Increased viability of the PHEV, for instance, through lower battery costs, higher running cost savings, or PHEV-promoting subsidies, will strengthen this effect. Therefore, a high share of viable PHEVs in the vehicle fleet does not necessarily result in a high share of electric driving. When designing policies to promote PHEVs, both the short- and long-term policy objectives and their potential effects need to be considered explicitly.

In previous works, we have shown two-car households to be better suited than one-car households for leveraging the potential benefits of the battery electric vehicle (BEV), both when the BEV simply replaces the second car and when it is used optimally in combination with a conventional car to overcome the BEV’s range limitation and increase its utilization. Based on a set of GPS-measured car movement data from 64 two-car households in Sweden, we here assess the potential electric driving of a plug-in hybrid electric vehicle (PHEV) in a two-car household and compare the resulting economic viability and potential fuel substitution to that of a BEV. Using estimates of near-term mass production costs, our results suggest that, for Swedish two-car households, the PHEV in general should have a higher total cost of ownership than the BEV, provided the use of the BEV is optimized. However, the PHEV will increasingly be favored if, for example, drivers cannot or do not want to optimize usage. In addition, the PHEV and the BEV are not perfect substitutes. The PHEV may be favored if drivers require that the vehicle be able to satisfy all driving needs (i.e., if drivers don’t accept the range and charge-time restrictions of the BEV) or if drivers requires an even larger battery in the BEV to counter range anxiety. We find that, given a particular usage strategy, the electric drive fraction (EDF) of the vehicle fleet is less dependent on whether PHEVs or BEVs are used to replace one of the conventional cars in two-car households. Instead, the EDF depends more on the usage strategy, i.e., on whether the PHEV/BEV is used to replace the conventional car with the higher annual mileage (“the first car”), the less used car (“the second car”), or is used flexibly to substitute for either in order to optimize use. For example, from a fuel replacement perspective it is often better to replace the first car with a PHEV than to replace the second with a BEV.

The use of an automatic transmission in pre-transmission parallel hybrid electric vehicles provides greater potential for powertrain optimization than conventional vehicles. By modifying the shift map, the transmission’s gear selection can be adjusted to reduce the energy consumption of the vehicle. A method for determining the optimal shift map for this hybrid vehicle has been implemented using global optimization and software-in-the-loop vehicle simulation. An analysis of the optimization has been performed using software-in-the-loop and hardware-in-the-loop simulation and evaluates two vehicle modes: regenerative braking active and regenerative braking disabled. The results of these two modes illustrate the successful implementation of the global optimization algorithm. However, the evaluation results raise practical concerns about implementing the optimized shift maps in a vehicle and illustrate a problem which must be overcome for future development.

Mississippi State University was selected for participation in the EcoCAR 3 Advance Vehicle Technology Competition. The team designed its architecture around the use of two UQM electric motors, and a Weber MPE 850cc turbocharged engine. To combine the three inputs into a singular output a custom gearbox was designed with seven helical gears. The gears were designed to handle the high torque and speeds the vehicle would experience. The use of this custom gearbox allows for a variety of control strategies. By optimizing the torque supplied by each motor, the overall energy consumption of the vehicle could be reduced. Additionally, studies were completed on the engine to understand the effects of injecting water into the engine’s intake manifold at 25% pedal request from 2000-3500 rpm. Overall, every speed showed an optimum at 20% water to fuel ratio, which obtained reductions in brake specific fuel consumption of up to 9.4%.

Indiana University-Purdue University Indianapolis (IUPUI) / Plug-in Hybrid Electric Vehicles (PHEV) are new generation Hybrid Electric Vehicles (HEV) with larger battery capacity compared to Hybrid Electric Vehicles. They can store electrical energy from a domestic power supply and can drive the vehicle alone in Electric Vehicle (EV) mode. According to the U.S. Department of Transportation 80 % of the American driving public on average drives under 50 miles per day. A PHEV vehicle that can drive up to 50 miles by making maximum use of cheaper electrical energy from a domestic supply can significantly reduce the conventional fuel consumption. This may also help in improving the environment as PHEVs emit less harmful gases. However, the Energy Management System (EMS) of PHEVs would have to be very different from existing EMSs of HEVs. In this thesis, three different Energy Management Systems have been designed specifically for PHEVs using simulated study. For most of the EMS development mathematical vehicle models for powersplit drivetrain configuration are built and later on the results are tested on advanced vehicle modeling tools like ADVISOR or PSAT. The main objective of the study is to design EMSs to reduce fuel consumption by the vehicle. These EMSs are compared with existing EMSs which show overall improvement. x In this thesis the final EMS is designed in three intermediate steps. First, a simple rule based EMS was designed to improve the fuel economy for parametric study. Second, an optimized EMS was designed with the main objective to improve fuel economy of the vehicle. Here Particle Swarm Optimization (PSO) technique is used to obtain the optimum parameter values. This EMS has provided optimum parameters which result in optimum blended mode operation of the vehicle. Finally, to obtain optimum charge depletion and charge sustaining mode operation of the vehicle an advanced PSO EMS is designed which provides optimal results for the vehicle to operate in charge depletion and charge sustaining modes. Furthermore, to implement the developed advanced PSO EMS in real-time a possible real time implementation technique is designed using neural networks. This neural network implementation provides sub-optimal results as compared to advanced PSO EMS results but it can be implemented in real time in a vehicle. These EMSs can be used to obtain optimal results for the vehicle driving conditions such that fuel economy is improved. Moreover, the optimal designed EMS can also be implemented in real-time using the neural network procedure described.

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The future smart grid is envisioned as a large scale cyber-physical system encompassing advanced power, computing, communications and control technologies. This work provides comprehensive accounts of the application with optimization methods, probability theory, commitment and dispatching technologies for addressing open problems in three emerging areas that pertain to the smart grid: unit commitment, service restoration problems in microgrid systems, and charging services for the plug-in hybrid electric vehicle (PHEV) markets. The work on the short-term scheduling problem in renewable-powered islanded microgrids is to determine the least-cost unit commitment (UC) and the associated dispatch, while meeting electricity load, environmental and system operating requirements. A novel probability-based concept, {\em probability of self-sufficiency}, is introduced to indicate the probability that the microgrid is capable of meeting local demand in a self-sufficient manner. Furthermore, we make the first attempt in approaching the mixed-integer UC problem from a convex optimization perspective, which leads to an analytical closed-form characterization of the optimal commitment and dispatch solutions. The extended research of the renewable-powered microgrid in the connection mode is the second part of this work. In this situation, the role of microgrid is changed to be either an electricity provider selling energy to the main grid or a consumer purchasing energy from the main grid. This interaction with the main grid completes work on the scheduling schemes. Third, a microgrid should be connected with the main grid most of the time. However, when a blackout of the main grid occurs, how to guarantee reliability in a microgrid as much as possible becomes an immediate question, which motivates us to investigate the service restoration in a microgrid, driven islanded by an unscheduled breakdown from the main grid. The objective is to determine the maximum of the expected restorative loads by choosing the best arrangement of the power network configurations immediately from the beginning of the breakdown all the way to the end of the island mode. Lastly, the work investigating the pricing strategy in future PHEV markets considers a monopoly market with two typical service classes. The unique characteristics of battery charging result in a piecewise linear quality of service model. Resorting to the concept of subdifferential, some theoretical results, including the existence and uniqueness of the subscriber equilibrium as well as the convergence of the corresponding subscriber dynamics are established. In the course of developing revenue-maximizing pricing strategies for both service classes, a general tradeoff has been identi ed between monetization and customer acquisition. / Graduate