<p>Hybrid electric vehicles are considered to be an important part of the future vehicle industry, since they decrease fuel consumption without decreasing the performance compared to a conventional vehicle. They use two or more power sources to propel the vehicle, normally one combustion engine and one electric machine. These power sources can be arranged in different topologies and can cooporate in different ways. In this thesis, dynamic models of parallel and series hybrid powertrains are developed, and different strategies for how to control them are compared.An optimization algorithm for decreasing fuel consumption and utilize the battery storage capacity as much as possible is also developed, implemented and tested.</p>

<p>Hybrid electric vehicles have two power sources - an internal combustion engine and an electric motor. These vehicles are of great interest because they contribute to a decreasing fuel consumption and air pollution and still maintain the performance of a conventional car. Different topologies are described in this thesis and especially the series and parallel hybrid electric vehicle and Toyota Prius have been studied. </p><p>This thesis also depicts modelling of a reference car and a series hybrid electric vehicle in Modelica. When appropriate, models from the Modelica standard library have been used. Models for a manual gearbox, final drive, wheel, chassis, air drag and a driver have been developed for the reference car. </p><p>For the hybrid electric vehicle a continuously variable transmission, battery, an electric motor, fuel cut-off function for the internal combustion engine and a converter that distributes the current between generator, electric motor and internal combustion engine have been designed. </p><p>These models have been put together with models from the Modelica standard library to a reference car and a series hybrid electric vehicle which follows the NEDC driving cycle. A sketch for the parallel hybrid electric vehicle and Toyota Prius have also been made in Modelica. </p><p>Developed models have been introduced into the Modelica library VehProLib, which is a vehicle propulsion library under development by Vehicular Systems, Linköpings universitet.</p>

Performance of two different waste heat recovery systems (one based on Rankine cycle and the other one using thermoelectricity) combined with non-hybrid, mild-hybrid and full hybrid systems are investigated. The vehicle under investigation was a 440hp Scania truck, loaded by 40 tons. Input data included logged data from a long haulage drive test in Sweden.All systems (waste heat recovery as well as hybrid) are implemented and simulated in Matlab/Simulink. Almost all systems are modeled using measured data or performance curves provided by one manufacturer. For Rankine system results from another investigation were used.Regardless of practical issues in implementing systems, reduction in fuel consumption for six different combination of waste heat recovery systems and hybrid systems with different degrees of hybridization are calculated. In general Rankine cycle shows a better performance. However, due to improvements achieved in laboratories, thermoelectricity could also be an option in future.This study focuses on “system” point of view and therefore high precision calculations is not included. However it can be useful in making decisions for further investigations.

The shift to strong hybrid and electrified vehicle architectures engenders controversy and brings about many unanswered questions. It is unclear whether developed markets will have the infrastructure in place to support and successfully implement them. To date, limited effort has been made to comprehend if the energy and transportation solutions that work well for one city or geographic region may extend broadly. A region's capacity to supply a fleet of EVs, or plug-in hybrid vehicles with the required charging infrastructure, does not necessarily make such vehicle architectures an optimal solution. In this study, a mix of technologies ranging from HEV to PHEV and EREV through to Battery Electric Vehicles were analyzed and set in three Canadian Provinces and 3 U.S. Regions for the year 2020. Government agency developed environmental software tools were used to estimate greenhouse gas emissions and energy use. Projected vehicle technology shares were employed to estimate regional environmental implications. Alternative vehicle technologies and fuels are recommended for each region based on local power generation schemes. / UOIT

This thesis takes EV from the late 90’s as a baseline, assess the capability of today’s EV technology, and establishes its near-term and long-term prospects. Simulations are performed to evaluate EVs with different combinations of new electric machines and battery chemistries. Cost assessment is also presented to address the major challenge of EV commercialization. This assessment is based on two popular vehicle classes: subcompact and mid-size. Fuel, electricity and battery costs are taken into consideration for this study. Despite remaining challenges and concerns, this study shows that with production level increases and battery price-drops, full function EVs could dominate the market in the longer term. The modeling shows that from a technical and performance standpoint both range and recharge times already fall into a window of practicality, with few if any compromises relative to conventional vehicles. Electric vehicles are the most sustainable alternative personal transportation technology available to-date. With continuing breakthroughs, minimal change to the power grid, and optimal GHG reductions, emerging electric vehicle performance is unexpectedly high.

The paradigm of personal transportation is changing. Electric vehicles are here. The arrival of the Tesla Roadster, Nissan Leaf, and Chevy Volt has changed the way in which we have to think about the energy that fuels our transportation needs. As PEVs find their way into garages this year and especially in the coming years, the neighborhood, city, state, and regional electric infrastructure will take on a new importance for many people as their interactions with it become significantly more complex and intimate as a result of regular electric vehicle charging.

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The owners of a house in today’s society do not know in real-time how much electricity they use. It could be beneficial for any residential consumer to have more control and overview in real-time over the electricity consumption. This could be done possible with a system that monitors the consumptions, micro renewables and the electricity prices from the grid and then makes a decision to either use or sell electricity to reduce the monthly electricity cost for the household and living a "Greener" life to reduce carbon emissions. In this thesis, estimations are made based on artificial neural network (ANN). The predictions are made for air temperature, solar insolation and wind speed in order to know how much energy will be produced in the next 24 hours from the solar panel and from the wind turbine. The predictions are made for electricity consumption in order to know how much energy the house will consume. These predictions are then used as an input to the system. The system has 3 controls, one to control the amount of sell or buy the energy, one to control the amount of energy to charge or discharge the fixed battery and one to control the amount of energy to charge or discharge the electric vehicle (EV). The output from the system will be the decision for the next 10 minutes for each of the 3 controls. To study the reliability of the ANN estimations, the ANN estimations (SANN) are compared with the real data (Sreal ) and other estimation based on the mean values (Smean) of the previous week. The simulation during a day in January gave that the expenses are 0.6285 € if using SANN, 0.7788 € if using Smean and 0.5974 € if using Sreal. Further, 3 different cases are considered to calculate the savings based on the ANN estimations. The first case is to have the system connected with fixed storage device and EV (Scon;batt ). The second and third cases are to have the system disconnected (without fixed battery) using micro generation (Sdiscon;micro) and not using micro generation (Sdiscon) along with the EV. The savings are calculated as a difference between Scon;batt and Sdiscon, also between Sdiscon;micro and Sdiscon. The saving are 788.68 € during a year if Scon;batt is used and 593.90 € during a year if Sdiscon;micro is used. With the calculated savings and the cost for the equipment, the pay-back period is 15.3 years for Scon;batt and 4.5 years for Sdiscon;micro. It is profitable to only use micro generation, but then the owner of the household loses the opportunity to be part of helping the society to become "Greener".

Hybrid electric vehicles are considered to be an important part of the future vehicle industry, since they decrease fuel consumption without decreasing the performance compared to a conventional vehicle. They use two or more power sources to propel the vehicle, normally one combustion engine and one electric machine. These power sources can be arranged in different topologies and can cooporate in different ways. In this thesis, dynamic models of parallel and series hybrid powertrains are developed, and different strategies for how to control them are compared.An optimization algorithm for decreasing fuel consumption and utilize the battery storage capacity as much as possible is also developed, implemented and tested.

Hybrid electric vehicles have two power sources - an internal combustion engine and an electric motor. These vehicles are of great interest because they contribute to a decreasing fuel consumption and air pollution and still maintain the performance of a conventional car. Different topologies are described in this thesis and especially the series and parallel hybrid electric vehicle and Toyota Prius have been studied. This thesis also depicts modelling of a reference car and a series hybrid electric vehicle in Modelica. When appropriate, models from the Modelica standard library have been used. Models for a manual gearbox, final drive, wheel, chassis, air drag and a driver have been developed for the reference car. For the hybrid electric vehicle a continuously variable transmission, battery, an electric motor, fuel cut-off function for the internal combustion engine and a converter that distributes the current between generator, electric motor and internal combustion engine have been designed. These models have been put together with models from the Modelica standard library to a reference car and a series hybrid electric vehicle which follows the NEDC driving cycle. A sketch for the parallel hybrid electric vehicle and Toyota Prius have also been made in Modelica. Developed models have been introduced into the Modelica library VehProLib, which is a vehicle propulsion library under development by Vehicular Systems, Linköpings universitet.