Due to an increasing concern of the introduction of greenhouse gas (GHG) regulations in many jurisdictions, the underground mining industry is in high demand to tackle climate change through innovative measures. In order to stay competitive, cope with rising energy costs and GHG regulations, mining companies will have to consider the alternative to go fully electric. As underground mines progress through time they are becoming deeper and deeper, resulting in longer haulage distances and thus an increasing energy demand. The research in this thesis was conducted to analyze and develop a simulation tool to investigate the replacement of conventional diesel haulage trucks with battery electric trucks that include a fast-charging capability in an underground mine environment. The results show that there is a major difference in the achievable production rates depending on the mine topography and a need for opportunity charging. Furthermore, the developed tool could aid in decision making and provide a good frame of reference of the feasibility of replacing an existing diesel operation by a battery electric one.

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.

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.

Electric Vehicles (EVs) are seen as one of the solutions to some of the world’s global current problems, such as global warming and air pollution, due to non-existent operational emissions and increased efficiency. There are multiple types of EVs, one of them being Battery Electric Vehicles (BEVs) which in most cases utilizes a Li-Ion battery pack as energy storage. Li-Ion batteries for EV applications are deemed to have reached End of Life (EoL) at 80%-70% of the battery’s initial energy capacity, the degradation is caused by calendar and cycle aging. Calendar aging is dependent on storage temperature and State of Charge (SoC), controlling these factors are therefore of importance when storing battery packs to minimize aging. Diagnostics of battery packs is also useful for determining second-life applications, State of Health (SoH) or other future usage. AFRY has therefore an interest in developing a product that would enable diagnostics and charging/discharging of off-vehicle battery packs, as regular chargers and tools are not compatible with battery packs separated from its vehicle. This thesis is a part of a project to develop a product that enables diagnostics and charging/discharging for different types off-vehicle battery packs. Due to time limitation of the thesis work this report focuses on the hardware design of the Power Conversion Module (PCM) from a charging/discharging perspective. This thesis project will propose a theoretical PCM from received requirements and choose appropriate components for this subsystemfrom a charging/discharging perspective. The design requirements were gathered through interviews, archive analysis and literature studies and argued for. This to achieve an understanding of the requirements that the system design needs to fulfill. A system design proposal of the PCM was presented and a component analysis of the included components was conducted. The proposed solution should in theory enable charging/discharging of battery packs, but further work and studies needs to be performed to validate the results in practice. Some calculations and variables were inferredwith the help of discussions, due to lack of information and time. The goal of the thesis was fulfilled, and the wider project objective was partially fulfilled within the boundaries of this thesis project.

Battery electric vehicles are becoming more common but still fall behind combustion engine cars in terms of driving range and charging time. The displayed driving range in electric vehicles' dashboard can be a volatile parameter suddenly dropping by 10-20\%, for instance when speed is increased. Which can result in a condition referred to as range anxiety . Hence it is interesting to observe more in detail how drivers behave and think in scenarios where range is important and the cars' available range can change drastically depending on the drivers driving style. Such scenarios are problematic to test in real traffic for practical and ethical reasons. In this article, without putting anyone at risk, we present a study using a VR driving simulator in a critical scenario with a substantial risk of running out of battery. Two separate groups (N=10) each drove on the same test track using two different range displays. One group had a typical range display showing the distance left to empty (out of battery) and the other group a novel and more transparent display. The novel display shows how speed is affecting the range. Both displays allow the driver to set a target driving range. The results indicate that the novel display allows for a more agile and adaptive driving style by changing between specific speeds rather than searching and "guessing" which speed is the most optimal as with typical range displays. Although, it can hide other affecting factors, such as acceleration and road height. Which was more prevalent amongst drivers who had to search and guess. / Batterielbilar blir allt vanligare men når inte riktigt upp till samma nivå som bilar med förbränningsmotorer när det handlar om räckvidd och laddtid. Den kvarstående körsträckan som visas i elbilars instrumentpanel kan vara en instabil variabel och plötsligt sjunka med 10-20%, när man till exempel ökar hastigheten. Vilket kan leda till ett tillstånd som kallas räckviddsångest . Därav intresset för att undersöka i detalj hur förare agerar och tänker i scenarier där räckvidd är extra viktigt och bilens kvarstående körsträcka kan ändras drastiskt beroende på körstil. Sådana scenarier är problematiska att testa ute i trafiken av både praktiska och etiska skäl. I denna artikel, utan att placera någon i en verklig riskfylld situation, presenterar vi en studie där en bilsimulator i VR används för att testa ett kritiskt scenario där risken för att strömmen tar slut är stor. Två separata grupper (N=10) körde samma sträcka fast med olika instrumentpaneler. Där den ena är mer konventionell och endast visar kvarstående körsträcka. Medan den andra är mer originell och visar hur hastighet påverkar kvarstående körsträcka. Båda instrumentpanelerna tillåter föraren att ställa in hur långt man vill köra. Resultaten indikerar på att den originella instrumentpanelen tillåter en mer agil och adaptiv körstil, genom att byta mellan specifika hastigheter istället för att leta och gissa vilken hastighet som är optimal, vilket skedde med den konventionella instrumentpanelen. Men den kan även dölja andra faktorer som påverkar körsträckan, såsom acceleration och höjdskillnader. Vilket  användare av den originella instrumentbrädan noterade i större utsträckning.

Considerable resources worldwide are invested in the research and development of future transportation technology. The foreseen direction and therefore research of future personalised transportation is focused on Battery Electric Vehicles (BEV) or hybrid combinations that use hydrogen fuel cells. These new transport energy systems are consider most to replace the current vehicles powered by the internal combustion engine (ICE). The research work presented in this thesis mainly focuses on the development of a software control system for future BEV prototype vehicles - a generic intelligent control system (GICS). The system design adopts a modular design concept and intelligent control. The whole system consists of four modules being communication, power supply, motor driver and transmission module. Each module uses a microcontroller as the brain and builds an embedded control system within the module. The control and communication between the modules is based on a group of specific parameters and the status of a state machine. In order to effectively implement intelligent control and simplify the system structure and programming, a generic intelligent fuzzy logic model that can be configured to a specific application with a near real-time buffered communication methodology is developed. The tests made on the fuzzy control model and the near real-time buffered communication gave a very positive outcome. The implementation of the fuzzy control and the communication methodology in each of the modules results in a communication between the modules with a steady speed, better reliability and system stability. These modules link together through the communication channels and form a multi-agent collaborative system (MACS). As the controllers are designed based on the parametric concept, the system is able to be implemented to future new modules and therefore allow prototype vehicle control systems to be developed more efficiently. The MACS is based on the core components of the control system - fuzzy logic controller (FLC), Serial Communication and Analogue input control software modules. Further work is carried out as an attempt to integrate the control software with a hardware design for a generic electric propulsion drive (GEPD). This thesis therefore outlines the design and considerations in software and hardware integration in addition to the GICS. The output from this thesis being the construction of soft programming modules for embedded microcontroller based control system has been accepted and presented at two international conferences; one in Wellington, New Zealand[1] the second in Acireale, Italy[2].

Considerable resources worldwide are invested in the research and development of future transportation technology. The foreseen direction and therefore research of future personalised transportation is focused on Battery Electric Vehicles (BEV) or hybrid combinations that use hydrogen fuel cells. These new transport energy systems are consider most to replace the current vehicles powered by the internal combustion engine (ICE). The research work presented in this thesis mainly focuses on the development of a software control system for future BEV prototype vehicles - a generic intelligent control system (GICS). The system design adopts a modular design concept and intelligent control. The whole system consists of four modules being communication, power supply, motor driver and transmission module. Each module uses a microcontroller as the brain and builds an embedded control system within the module. The control and communication between the modules is based on a group of specific parameters and the status of a state machine. In order to effectively implement intelligent control and simplify the system structure and programming, a generic intelligent fuzzy logic model that can be configured to a specific application with a near real-time buffered communication methodology is developed. The tests made on the fuzzy control model and the near real-time buffered communication gave a very positive outcome. The implementation of the fuzzy control and the communication methodology in each of the modules results in a communication between the modules with a steady speed, better reliability and system stability. These modules link together through the communication channels and form a multi-agent collaborative system (MACS). As the controllers are designed based on the parametric concept, the system is able to be implemented to future new modules and therefore allow prototype vehicle control systems to be developed more efficiently. The MACS is based on the core components of the control system - fuzzy logic controller (FLC), Serial Communication and Analogue input control software modules. Further work is carried out as an attempt to integrate the control software with a hardware design for a generic electric propulsion drive (GEPD). This thesis therefore outlines the design and considerations in software and hardware integration in addition to the GICS. The output from this thesis being the construction of soft programming modules for embedded microcontroller based control system has been accepted and presented at two international conferences; one in Wellington, New Zealand[1] the second in Acireale, Italy[2].

Considerable resources worldwide are invested in the research and development of future transportation technology. The foreseen direction and therefore research of future personalised transportation is focused on Battery Electric Vehicles (BEV) or hybrid combinations that use hydrogen fuel cells. These new transport energy systems are consider most to replace the current vehicles powered by the internal combustion engine (ICE). The research work presented in this thesis mainly focuses on the development of a software control system for future BEV prototype vehicles - a generic intelligent control system (GICS). The system design adopts a modular design concept and intelligent control. The whole system consists of four modules being communication, power supply, motor driver and transmission module. Each module uses a microcontroller as the brain and builds an embedded control system within the module. The control and communication between the modules is based on a group of specific parameters and the status of a state machine. In order to effectively implement intelligent control and simplify the system structure and programming, a generic intelligent fuzzy logic model that can be configured to a specific application with a near real-time buffered communication methodology is developed. The tests made on the fuzzy control model and the near real-time buffered communication gave a very positive outcome. The implementation of the fuzzy control and the communication methodology in each of the modules results in a communication between the modules with a steady speed, better reliability and system stability. These modules link together through the communication channels and form a multi-agent collaborative system (MACS). As the controllers are designed based on the parametric concept, the system is able to be implemented to future new modules and therefore allow prototype vehicle control systems to be developed more efficiently. The MACS is based on the core components of the control system - fuzzy logic controller (FLC), Serial Communication and Analogue input control software modules. Further work is carried out as an attempt to integrate the control software with a hardware design for a generic electric propulsion drive (GEPD). This thesis therefore outlines the design and considerations in software and hardware integration in addition to the GICS. The output from this thesis being the construction of soft programming modules for embedded microcontroller based control system has been accepted and presented at two international conferences; one in Wellington, New Zealand[1] the second in Acireale, Italy[2].

The Swedish car fleet is currently amidst a transition of electrification. This increases the need for an extensive charging infrastructure, and thereby smoothly functioning payment methods for charging. At the time being, there are many charging operators in the market that provide their own payment solutions for charging Battery Electric Vehicles (BEV) and Plug-­in Hybrid Electric Vehicles (PHEV), as the market has developed without any regulations. In consideration of this problem definition, the possibilities and challenges for developing a common payment system was analyzed. With this aim, three key areas were studied: Firstly, the prerequisites for a common payment system in the market was investigated through the historical evolution of such a system in the banking industry. From this, parallels could be drawn to the current market situation of the BEV and PHEV charging industry. Secondly, the problematization was further researched in regard to the customer perspective of the current payment processes. Finally, the prerequisites for a common payment system was analyzed in regard to a company perspective. The three areas were researched through the following three methods: a literary analysis, a questionnaire and a field study at a company. The results show that a need for a unification of payments is present in heterogeneous markets. Therefore, the BEV and PHEV charging market has adequate preconditions for the development of a common payment system considering the innumerable amount of charging operators that currently exist in the market. Furthermore, the results from the questionnaire showed that a majority of BEV and PHEV users are unsatisfied with the current conformation of the payment processes. Lastly, the results show that in regard to the company perspective, there is a satisfactory market climate for entry of a common payment solution considering the business model and technological solution of the analyzed company as well as the customer need. / I takt med att Sveriges bilflotta elektrifieras ökar även behovet av en utbredd laddinfrastruktur och med det ett smidigt sätt att betala för laddningen. I dagsläget tillhandahåller många laddoperatörer egna betalningslösningar för laddning av el­ och laddhybridbilar då marknadens framväxt skett utan reglering. Utifrån denna problemformulering undersöktes möjligheter och utmaningar för ett gemensamt betalningssystem. Under studiens gång undersöktes i detta syfte tre områden: För det första utforskades förutsättningar för ett gemensamt betalningssystem genom att dra historiska paralleller från utvecklingen av ett sådant system inom bankindustrin. För det andra undersöktes problematiseringen utifrån ett kundperspektiv kring dagens betalningslösningar. Slutligen analyserades förutsättningarna för ett gemensamt betalningssystem ur ett företagsperspektiv. Områdena undersöktes genom följande tre metoder; en litteraturstudie, en enkätstudie och en fältstudie på ett företag. Resultaten visar att ett behov av enhetliga betalningar uppstår i samband med heterogena marknader. Därmed har marknaden för laddning av el­ och laddhybridbilar idag goda förutsättningar för ett gemensamt betalningssystem utifrån den variation av laddoperatörer på dagens marknad. Vidare visade enkätresultaten att en majoritet av el­ och laddhybridbilsägare är missnöjda gällande utformningen av dagens betalningsprocesser. Slutligen visade resultaten ur ett företagsperspektiv att det finns goda förutsättningar för introducering av en gemensam betalningslösning utifrån analys av affärsmodell, teknologisk lösning och kundbehov.

As the transport industry shifts towards Battery Electric Vehicles (BEVs) the need for accurate route planning rises. BEVs have reduced range compared to traditional fuel based vehicles, and the range can vary greatly depending on ambient conditions and vehicle load. Existing research focuses more on the theoretical algorithms, and often have none or very simple vehicle models, leaning towards consumer cars instead of heavy duty trucks. Vehicle Route Planning (VRP) is a wide research area, and this thesis focuses on the Shortest Path subproblem. Contraction Hierarchies (CHs) is a commonly used family of algorithms for finding shortest paths in road networks, and is prevalent in the research frontier. CHs however comes with certain drawbacks, such as having to perform a costly preprocessing phase whenever metrics change, and not being able to share map data between multiple vehicles in a fleet. This thesis extends CHs to support a mixed fleet, with fast metric updates and support for more detailed cost optimization goals. This is done by implementing Customizable Contraction Hierarchies (CCHs), but with custom data structures and customization phase. This implementation allows map data to be shared between vehicles in a fleet, and keeps each vehicle's edge weights separate. The edge weights can be updated quickly, as the customization phase scales linearly with the size of the map. The implementation also supports edge weights that do not adhere to triangle inequality, which the previous research did not. Experiments are executed on a map of Stockholm and a synthetic map, to test the algorithm's performance, verify correctness, and stress the importance of accurate metrics for optimization goals. The CCH performed as expected, if not better, and its correctness is upheld. The implementation is fit to be integrated into a route planner, but further research should be conducted to see how it meshes with other parts of VRP, such as time windows, turn costs, and charging stations. / När transportindustrin övergår till batterielektriska fordon ökar behovet av rigorös ruttplanering. Batterielektriska fordon har minskad räckvidd jämfört med traditionella bränslebaserade fordon, och räckvidden kan variera stort beroende på omgivningsförhållanden och fordonets belastning. Existerande forskning fokuserar mer på de teoretiska algoritmerna och har ofta inga eller mycket enkla fordonsmodeller, som liknar mer konsumentbilar istället för tunga lastbilar. Ruttplanering är ett brett forskningsområde, och denna avhandling fokuserar på underproblemet att hitta kortaste vägen. Kontraktionshierarkier är en välanvänd familj av algoritmer för att hitta kortaste vägen i ett vägnät, och är prevalent i forskningsfronten. Kontraktionshierarkier har dock vissa nackdelar, som att de behöver utföra en kostsam förbehandlingsfas när parametrar ändras, och att kartdatan inte kan delas mellan flera fordon i en flotta. Den här avhandlingen utökar Kontraktionshierarkier för att stödja en blandad fordonsflotta, med snabba uppdateringar av parametrar och stöd för mer detaljerade optimeringsmål. Detta görs genom att implementera Anpassningsbara Kontraktionsierarkier, men med anpassade datastrukturer och anpassningsfas. Denna implementering tillåter att kartdata delas mellan fordonen i en flotta, och håller varje fordons kantvikter separat. Kantvikterna kan uppdateras snabbt, eftersom anpassningsfasen skalas linjärt med storleken på kartan. Implementationen stöder också kantvikter som inte följer triangelojämlikheten, vilket den tidigare forskningen inte gjorde. Experiment utförs på en karta över Stockholm och en syntetisk karta, för att testa algoritmens prestanda, verifiera korrekthet, och betona vikten av detaljerade parametrar i optimeringsmål. Anpassningsbara Kontraktionshierarkier presterade som förväntat, om inte bättre, och dess korrekthet uppehölls. Implementeringen är lämplig för att integreras i en ruttplanerare, men ytterligare forskning bör genomföras för att se hur den passar ihop med andra delar av ruttplaneringsproblemet, så som tidsfönster, svängkostnader och laddstationer.