Battery Electric Vehicles and Plug-in Hybrid Vehicles are increasingly becoming more popular in recent years. Stricter regulations from government agencies to curb emissions and reduce impact on climate have led to automobile makers adopt electric powertrains. Eco-Routing is one such method to reduce energy usage in personal transport. EcoRouting is a methodology that determines the route with the least energy consumption between two points. Standard navigation systems often determine the shortest or the fastest route, emphasizing travel time. EcoRouting considers an alternative criterion - energy consumption. In this thesis, an automation methodology is presented that determines the EcoRoute among given route alternatives based on route distance, speed limits, road grades, traffic signs, driver aggression and the powertrain. There are three major objectives in this thesis: Developing the automation methodology for the determination of EcoRoute for use in on-board applications, validating the EcoRouting methodology on actual driving conditions and studying the impact of traffic on the choice of EcoRoute. The automation methodology has been developed on the Android framework for use with on-board applications on Android mobile devices. The automation methodology used to conduct sensitivity studies show that factors such as driver aggression, distance and conditional stops impact energy consumption. The comparison of results of simulation using the automation methodology against results from actual driving to validate the methodology on actual driving conditions show that transient traffic conditions can have significant impact on energy consumption. Finally, route energy consumptions for various traffic conditions are estimated using simulation to understand the impact of traffic on energy consumption and EcoRoute choice. Results that are obtained show that apart from traffic affecting the energy consumption, travel times can have an impact on choice of EcoRoute. / Master of Science / Government agencies have been introducing tighter regulations in order to improve fuel economy and reduce emissions. These regulations are targeted at reducing the impact of vehicle usage on climate. Automobile manufacturers have increasingly adopted electric powertrains to meet these regulations. Battery Electric Vehicles and Plug-in Hybrid Vehicles are more popular than ever. Other methods in reducing environmental impact by automobiles are also being conducted. EcoRouting is one such method. EcoRouting determines the route that consumes the least energy between two locations. EcoRouting requires no modifications to be done on the vehicle or its powertrain. A methodology has been developed in this thesis that takes into account various factors such as traffic signs, speed limits, road grades, powertrain and driver aggression to determine the route that consumes the least energy. Research in this thesis has been divided into three major parts: development of the automation methodology, validating the methodology for actual driving conditions and understanding the impact of traffic on energy consumption. Results of case studies show that the input parameters affect energy consumption significantly. Traveling speeds affect the energy consumption and since transient traffic conditions can affect traveling speeds, transient traffic conditions can have a significant impact on energy consumption. Since energy consumption alone is not considered in determining the EcoRoute and the travel times are also considered so as to not inconvenience the user, traffic conditions impact the choice of EcoRoute both due to differences in energy consumption and travel time.

Automotive manufacturers are facing increasing pressure from legislative bodies and consumers to reduce fuel consumption and greenhouse gas emissions of vehicles. This has led to many automotive manufacturers starting production of Plug-in Hybrid Electric Vehicles (PHEV's) and Battery Electric Vehicles (BEV's). Another method that helps to reduce the environmental effect of transportation is EcoRouting. The standard Global Positioning System (GPS) navigation offers route alternatives between user specified origin and destination. This technology provides multiple routes to the user and focuses on reducing the travel time to reach to the destination. EcoRouting is the method to determine a route that minimizes vehicle energy consumption, unlike traditional routing methods that minimize travel time. An EcoRouting system has been developed as a part of this thesis that takes in information such as speed limits, the number of stop lights, and the road grade to calculate the energy consumption of a vehicle along a route. A synthesis methodology is introduced that takes into consideration the distance between the origin and destination, the acceleration rate of the vehicle, cruise speed and jerk rate as inputs to simulate driver behavior on a given route. A new approach is presented in this thesis that weighs the energy consumption for different routes and chooses the route with the least energy consumption, subject to a constraint on travel time. A cost function for quantifying the effect of travel time is introduced that assists in choosing the EcoRoute with an acceptable limit on the travel time required to reach the destination. The analysis of the EcoRouting system with minimum number of conditional stops and maximum number of conditional stops is done in this thesis. The effect on energy consumption with the presence and absence of road-grade information along a route is also studied. A sensitivity study is performed to observe the change in energy consumption of the vehicle with a change in acceleration rates and road grade. Three routing scenarios are presented in this thesis to demonstrate the functionality of EcoRouting. The EcoRouting model presented in this thesis is also validated against an external EcoRouting research paper and the energy consumption along three routes is calculated. The EcoRoute solution is found to vary with the information given to the variable acceleration rate model. The synthesis and the results that are obtained show that parameters such as acceleration, deceleration, and road grade affect the overall energy consumption of a vehicle and are helpful in determining the EcoRoute. / Master of Science / The automotive industry is undergoing a major transformation throughout the world in terms of regulations on greenhouse gas emissions and fuel consumption. There is a significant amount of research being done on reducing emissions of cars while maintaining safety, performance and consumer acceptability of vehicles with an emphasis on cost and innovation. Vehicle manufacturers have started manufacturing Plug-In Hybrid Electric Vehicles (PHEV’s) and Battery Electric Vehicles (BEV’s) with a focus on reducing petroleum use. While a lot of work is being done on manufacturing cars that help reduce emissions, significant research is also being conducted to help navigate cars in an energy efficient manner. EcoRouting is defined as the method that helps to route cars efficiently and conserve energy. EcoRouting helps to increase fuel efficiency without any modifications to the vehicle powertrain and can be customized to any vehicle. A simulation study to analyze the effects of EcoRouting in different driving conditions with an emphasis on the effects of road grade and stop lights on energy consumption is presented. The EcoRoute solution is found to vary with the road grade, the maximum allowed acceleration, and the number of conditional traffic lights. The synthesis and the results that are obtained show that external parameters such as road grades, speed limits, and stop lights affect the overall energy consumption of a vehicle and that EcoRouting can significantly reduce vehicle energy consumption. The EcoRouting research done in this thesis focuses mainly on analyzing the effect of changes in road grade and accelerations on the energy consumption of a vehicle. A sensitivity study is performed to study the change in energy consumption of a vehicle with a change in road grade and acceleration. It is found that the net difference in elevation between the origin and the destination plays a significant role in determining the energy consumption of a vehicle. This thesis also focuses on formulating a cost function for the maximum permissible travel time required to reach the destination and shows how travel time is an important metric to determine an EcoRoute. Three case studies are presented which provide a demonstration of the discussed methods and typify a working EcoRouting model.

The automotive industry is facing some of the most difficult design challenges in industry history. Developing innovative methods to reduce fossil fuel dependence is imperative for maintaining compliance with government regulations and consumer demand. In addition to powertrain design, route selection contributes to vehicle environmental impact. The objective of this thesis is to develop a methodology for evaluating the energy consumption of each route option for a specific vehicle. A 'backwards' energy tracking method determines tractive demand at the wheels from route requirements and vehicle characteristics. Next, this method tracks energy quantities at each powertrain component. Each component model is scalable such that different vehicle powertrains may be approximated. Using an 'ecorouting' process, the most ideal route is selected by weighting relative total energy consumption and travel time. Only limited powertrain characteristics are publicly available. As the future goal of this project is to apply the model to many vehicle powertrain types, the powertrain model must be reasonably accurate with minimal vehicle powertrain characteristics. Future work expands this model to constantly re-evaluate energy consumption with real-time traffic and terrain information. While ecorouting has been applied to conventional vehicles in many publications, electrified vehicles are less studied. Hybrid vehicles are particularly complicated to model due to additional components, systems, and operation modes. This methodology has been validated to represent conventional, battery electric, and parallel hybrid electric vehicles. A sensitivity study demonstrates that the model is capable of differentiating powertrains with different parameters and routes with different characteristics. / Master of Science