Energy production is associated with environmental impairment. Most anxious is the greenhouse gas emissions, which also arise from transportation. If battery electric vehicles should be able to alleviate the problem, they must be charged with environmentally friendly produced electricity. This paper investigates a possible relationship between battery electric vehicles and solar photovoltaic panels in household survey data from ENABLE.EU performed in ten European countries autumn 2017 – spring 2018. Estimated with a logit binary choice model, it is found that the probability that a household owns a battery electric vehicle increases if the household owns solar photovoltaic panels. Furthermore, this increase in probability is higher within countries with a higher market diffusion of battery electric vehicle and solar photovoltaic panels (France and the UK). This suggests that policy encouraging home charging of battery electric vehicles from solar photovoltaic panels that includes an energy storage facility could speed up the transition of the vehicle fleet.

Battery electric buses (BEBs) bring several advantages to public transportation systems. With fixed routes and scheduled trips, the implementation of BEBs in the transit context is considered a seamless transition towards a zero greenhouse gases transit system. However, energy consumption uncertainty is a significant deterrent for mainstream implementation of BEBs. Demonstration and trial projects are often conducted to better understand the uncertainty in energy consumption (EC). However, the BEB's energy consumption varies due to uncertainty in operational, topological, and environmental attributes. This thesis aims at developing simulation, data-driven, and low-resolution models using big data to quantify the EC of BEBs, with the overarching goal of developing a comprehensive planning framework for BEB implementation in bus transit networks. This aim is achieved through four interwind objectives. 1) Quantify the operational and topological characteristics of bus transit networks using complex network theory. This objective provides a fundamental base to understanding the behaviour of bus transit networks under disruptive events. 2) Investigate the impacts of the vehicular, operational, topological, and external parameters on the EC of BEBs. 3) Develop and evaluate the feasibility of big-data analytics and data-driven models to numerically estimate BEB's EC. 4) Create an open-source low-resolution data-based framework to estimate the EC of BEBs. This framework integrates the modelling efforts in objectives 1-3 and offers practical knowledge for transit providers. Overall, the thesis provides genuine contributions to BEB research and offers a practical framework for addressing the EC uncertainty associated with BEB operation in the transit context. Further, the results offer transit planners the means to set up the optimum transit operations profile that improves BEB energy utilization, and in turn, reduces transit-related greenhouse gases. / Thesis / Doctor of Engineering (DEng)

Background:Rising greenhouse gas levels through the use of traditional ICE technology in the transport industry have created a worldwide environmental crisis. Battery Electric Bus adoption is a prominent alternative currently being discussed in the public transport industry and represents an inevitable change towards a sustainable future. Purpose:The establishment of a theoretical framework that analyzes primary and secondary data todefine the factors promoting BEB implementation. Method:The study follows a qualitative research approach gathering data in the form of semi-structured interviews which are analyzed to develop an objective theory. Conclusion:The results show that the primary factors influencing diffusion of BEBs are technology factors, macro-economic factors, and socio-political factors. The research defines the relationships between them to further understand their effects on BEB diffusion. The findings develop a theoretical framework around these factors and their effects on one another and the diffusion of BEBs in the industry.

Thermal expansion can be an issue in solid busbars, the expansion is caused by several factors and can cause plastic deformation in connection points or structure around it. The expansion occurs due to temperature differences in the busbar as a result of altered ambient temperature and/or joule heating. The environment where a vehicle is used can be harsh and varying in temperatures a lot. For future fast charging systems, a high amount of current will be passed in the conductors. In a stationary installation, this could be solved by increasing the cross-section area. In vehicles, the weight, cost, and space limitations callfor optimization of the conductor. In this thesis, there are several geometrical alterations done to the busbar to investigate the possibility to reduce the amount of stress acting on the connection points. The main geometrical evaluation is to compare a straight busbar to a U-shaped busbar. In the U-shape, the height, bend radius, and cross-section shape are investigated. To investigate this issue a simulation model was developed using Comsol, this software was used to evaluate stress values, max temperature, losses, and displacement. The results from the simulation showed that the U-shape has a large potential to reduce the amount of stress. Also, the cross-section shape tests showed that the steady-state temperature was lower for the more flatter shaped busbar. This is true both for the U-shape and straight busbar. This resulted inreduced amount of thermal expansion causing lower amount of stress, without adding any weight. The weight parameter is extremely important for vehicle implementation. The last test is looking at the busbar material where nickel-plated copper is compared to anodized aluminum. This test is divided into two parts, the first one is looking at an aluminum busbar compared to a copper busbar of the same geometry. This test showed that the losses in the aluminum busbar were much higher, but the steady-state temperature and max stress were lower. The second part of the test investigated the compensated aluminum busbar, this one is modeled by compensating the cross-section area for the higher resistance value of aluminum. The results from this busbar compared to the standard-shaped busbar showed a substantially lower stress, temperature and weight. But the overall dimensions are larger due to the compensated cross-section area. Having this larger Cross section area might hinder the implementation of aluminium busbars in parts of the vehicle where there is a lack of space, like in a battery box. / Termisk expansion i solida busbars är ett vanligt problem vid kraftig temperaturvariation. Problemet ökar med längden av busbaren och kan leda till plastisk deformation i infästningen av busbaren. Temperaturvariationen kan ske genom varierad omgivningstemperatur eller genom resistiv uppvärmning. Om en busbar ska användas i ett fordon för kraftöverföring är arbetsmiljön mycket påfrestande. Den termiska uppvärmningen går normalt att motverka genom att öka tvärsnittsarean, men i ett fordon där vikt, kostnad och platsbrist minskar möjligheten för ökad tvärsnittsarea blir optimering av ledaren extra viktig. För att undersöka problemet utvecklades en simuleringsmodell med hjälp av Comsol. Denna programvara använder för att utvärdera spänningskoncentrationer, maxtemperatur, förluster och utböjningar i busbaren. För att undersöka eventuella lösningar togs det fram flera geometriska variationer till busbaren, där möjligheten att använda en “U-form” utgjorde basen i en jämförelse mot en vanlig rakbusbar. För U-formen undersöktes U-höjden, böj-radien samt tvärsnittsformen. Även en jämförelse mellan nickelpläterad koppar och anodiserad aluminiumgenomfördes för att urskilja eventuella för och nackdelar med materialen. Resultaten från simuleringarna visade att U-formen gav klart lägre spänning i kontaktpunkterna. Även tvärsnittsformen påverkade temperaturen och spänningen i busbaren, där den plattare varianten presterade bättre på alla parametrar som undersöktes i simuleringen. För utvärderingen av materialet utfördes två tester, det första testet jämför en busbar i aluminium mot en i koppar med exakt samma geometri, detta testvisade att temperaturen samt spänningen blir lägre i aluminiumvarianten, dock ökar förlusterna kraftigt då aluminium har högre resistans än koppar. I den andra testet användes en kompenserad aluminiumbusbar där tvärsnittsarean har ökats för att ge samma resistans som kopparvarianten. Denna busbar fick en mycket lägre sluttemperatur, spänning och vikt. Förlusterna blev detsamma. Den högre tvärsnittsarean ger dock en fysiskt större busbar.

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

Manufacturers of passenger vehicles are experiencing increased pressure from consumers and legislators due to the impact of transportation on the environment. Automotive manufacturers are responding by designing more sustainable forms of transportation through a variety of efforts, including increased vehicle efficiency and the electrification of vehicle powertrains (plug in hybrid electric vehicles (PHEV) and battery electric vehicles (BEV)). An additional method for reducing the environmental impact of personal transport is eco-routing, a methodology which selects routes on the basis of energy consumption. Standard navigation systems offer route alternatives between a user clarified origin and destination when there are multiple paths available. These alternatives are commonly weighted on the basis of minimizing either total travel time (TTT) or trip distance. Eco-routing offers an alternative criterion – minimizing route energy consumption. Calculation of the energy consumption of a route necessitates the creation of a velocity profile which models how the route will be driven and a powertrain model which relates energy consumption to the constructed velocity profile. Existing research efforts related to both of these aspects typically require complex analysis and proprietary vehicle properties. A new approach to weighting the energy consumption of different routes is presented within this paper. The process of synthesizing velocity profiles is an improvement upon simpler models while requiring fewer variables as compared to more complex models. A single input, the maximum acceleration, is required to tune driver aggressiveness throughout an entire route. Additionally, powertrain results are simplified through the application of a new parameter, predictive terminal energy. The parameter uses only glider properties as inputs, as compared to dedicated powertrain models which use proprietary vehicle information as inputs which are not readily available from manufacturers. Application of this research reduces computation time and increases the number of vehicles for which this analysis can be applied. An example routing scenario is presented, demonstrating the capability of the velocity synthesis and predictive terminal energy methodologies. / Master of Science

Due to increased urgency regarding environmental concerns within the transportation industry, sustainable solutions for combating climate change are in high demand. One solution is a widespread transition from internal combustion engine vehicles (ICEVs) to battery electric vehicles (BEVs). To facilitate this transition, reliable energy consumption modeling is desired for providing quick, high-level estimations for a BEV without requiring extensive vehicle and computational resources. Therefore, the goal of this paper is to create a simple, yet reliable vehicle model, that can estimate the energy consumption of most, if not all, electric vehicles on the market by using parameter normalization techniques. These vehicle parameters include the vehicle test weight and performance to obtain a unified net Willans line to describe the input/output power through a linear relationship. A base model and three normalized models are developed by fitting the UDDS and HWFET energy consumption test data published by the EPA for all BEVs in the U.S. market. Out of the models analyzed, the normalization with weight performs best with the lowest RMSE values at 0.384 kW, 0.747 kW, and 0.988 kW for predicting the UDDS, HWY, and US06 data points, respectively, and 0.653 kW for all three data sets combined. Consideration of accessory loads at 0.5 kW improves the model normalized by weight and performance by a reduction of over 20% in RMSE for predictions with all data sets combined. Removing outliers in addition to consideration of accessory loads improves the model normalized by weight and performance by a reduction of over 36% in RMSE for predictions with all data sets combined. Overall, results suggest that a unified net Willans line is largely achievable with accessible energy consumption data on U.S. regulatory cycles. / Master of Science / Due to increased urgency regarding environmental concerns within the transportation industry, sustainable solutions for combating climate change are in high demand. One solution is a widespread transition from conventional internal combustion engine vehicles (ICEVs) to battery electric vehicles (BEVs). To facilitate this transition, reliable energy consumption modeling is desired to support quick, high-level analyses for BEVs without requiring expensive resources. Therefore, the goal of this paper is to create a simple vehicle model that can estimate the energy consumption of most, if not all, electric vehicles by scaling the data using vehicle parameters. These parameters include the vehicle test weight and performance to obtain a unified net Willans line model describing the input/output power through a linear relationship. The UDDS (city) and HWFET (highway) energy consumption data points used to develop the model are easily accessible from published EPA data. Out of the models analyzed, the normalization with test weight performs best with the lowest error values at 0.384 kW, 0.747 kW, and 0.988 kW for predicting the UDDS, HWFET, and US06 (aggressive city/highway cycle) data points, respectively, and 0.653 kW for all three data sets combined. Consideration of accessory loads at 0.5 kW improves the model normalized by weight and performance by a reduction of over 20% in error for predictions with all data sets combined. Removing outliers in addition to consideration of accessory loads improves the model normalized by weight and performance by a reduction of over 36% in error for predictions with all data sets combined. Overall, results suggest that a unified net Willans line is largely achievable with accessible energy consumption data on U.S. regulatory cycles.

Automotive vehicle manufacturers have been facing increased pressures from legislative bodies and consumers to reduce the fuel consumption and harmful emissions of their newly produced vehicles as a result of new research showing the detrimental effects these emissions have on the environment. These pressures are encouraging manufactures and researchers to invest billions of dollars into the development of new advanced vehicle technologies. Some of these investments have resulted in substantial progress in powertrain technologies that have led to the preliminary adoption of electrified powertrain vehicles. Other areas of research are actively working to reduce the energy consumption of a vehicle, regardless of its powertrain, by influencing driver behavior and by optimizing the way a vehicle travels between an origin and destination. This intelligent vehicle routing is done by analyzing a range of possible routes and selecting the route that consumes the least amount of fuel. An accurate method for predetermining vehicle energy expenditure along a given route before it is driven is needed to effectively implement intelligent vehicle routing systems. One common method is the generation of a road network-wide database with energy use figures for each section of road. This method requires expensive experimentation trials or network simulation software. Individual-level vehicle predictive energy estimation eliminates the need for costly fuel use generation by utilizing vehicle velocity generation techniques and vehicle powertrain models. Estimation of individual vehicle energy consumption along a route is done by identifying an origin-destination pair, detecting required full-stops along the path, and synthesizing multiple stop-to-stop velocity modes between each set of stops. The resulting velocity profile is paired with a specific vehicle powertrain model to determine fuel consumption. A drawback of this route generation technique is that the vehicle path is assumed to be one-dimensional and lacks inclusion of road curves and their associated velocity changes to maintain passenger comfort. This thesis evaluates the merit of discounting road curves in predictive vehicle energy consumption analyses and presents a technique for modeling common road corners that require velocity changes to limit passenger discomfort. The resulting corner synthesis method is combined with a validated vehicle powertrain model to complete full route consumption modeling. Two routes, an urban and highway, are modeled and driven to evaluate the accuracy of the full simulation model when compared with on-road data. The results show that corners can largely be ignored during energy consumption analysis for highways. The cornering effects on a vehicle during urban driving, however, should be included in urban route analyses with multiple road curves. Inclusion of the cornering effects during an example urban route analysis decreased the error between the on-road consumption data and the simulation results. / Master of Science

In this thesis, two electric vehicles are compared, a fuel cellpowered vehicle and a battery powered vehicle with a conventionalvehicle with an internal combustion engine. The comparison wasdone as a life cycle assessment and consisted of two stages, avehicle stage and a fuel stage. The vehicle stage consisted ofeverything from mining minerals to recycling of the vehicles,every aspect that’s connected to the car. The fuel stage consistedof fuel production and use during the vehicle’s lifetime. The fuelconsist of electricity and hydrogen produced through electrolysis. The goal of the thesis was to understand what aspects of thelifecycle matters most in terms greenhouse gases for each of theelectric vehicles. Since there are no emissions in terms ofgreenhouse gases while driving the electric vehicles, only fuelproduction, electricity and hydrogen through electrolysis, countedtowards the fuel stage. For the vehicle with an internalcombustion engine the fuel stage consisted of gasoline productionand emissions from driving. The results showed that when comparing electric vehicles withinternal combustion vehicles, the most important aspect was theelectricity mix, with a Nordic electricity mix for most use casesthe electric vehicles where more climate friendly then theinternal combustion vehicles. The fuel cell powered vehicle usedmore electricity than the battery powered vehicle when usingelectrolysis to create hydrogen, and therefore was more sensitiveto increases in emissions from the electricity mix. When comparingthe vehicle stage, battery production causes the most emissionsfor the battery powered vehicle and the hydrogen tank caused themost emissions for the fuel cell powered vehicle.

Battery electric vehicles (BEVs) could reduce CO2 emissions from the transport sector but their limited electric driving range diminishes their utility to users. The effect of the limited driving range can be reduced in multi-car households where users could choose between a BEV and a conventional car for long-distance travel. However, to what extent the driving patterns of different cars in a multi-car household’s suit the characteristics of a BEV needs further analysis. In this paper we analyse the probability of daily driving above a fixed threshold for conventional cars in current Swedish and German car driving data. We find second cars in multi-car households to require less adaptation and to be better suited for BEV adoption compared to first cars in multi-car households as well as to cars in single-car households. Specifically, the share of second cars that could fulfil all their driving is 20 percentage points higher compared to first cars and cars from single-car households. This result is stable against variation of driving range and of the tolerated number of days requiring adaptation. Furthermore, the range needed to cover all driving needs for about 70% of the vehicles is only 220 km for second cars compared to 390 km for the average car. We can further confirm that second cars have higher market viability from a total cost of ownership perspective. Here, the second cars achieve a 10 percentage points higher market share compared to first cars, and to cars in single-car households for Swedish economic conditions, while for Germany the corresponding figure is 2 percentage points. Our results are important for understanding the market viability of current and near-future BEVs.