On the eve of the large-scale introduction of electric vehicles, policy makers have to decide on how to organise a significant growth in charging infrastructure to meet demand. There is uncertainty about which charging deployment tactic to follow. The main issue is how many of charging stations, of which type, should be installed and where. Early roll-out has been successful in many places, but knowledge on how to plan a large-scale charging network in urban areas is missing. Little is known about return to scale effects, reciprocal effects of charger availability on sales, and the impact of fast charging or more clustered charging hubs on charging preferences of EV owners. This paper explores the effects of various roll-out strategies for charging infrastructure that facilitate the large-scale introduction of EVs, using agent-based simulation. In contrast to previously proposed models, our model is rooted in empirically observed charging patterns from EVs instead of travel patterns of fossil fuelled cars. In addition, the simulation incorporates different user types (inhabitants, visitors, taxis and shared vehicles) to model the diversity of charging behaviours in an urban environment. Different scenarios are explored along the lines of the type of charging infrastructure (level 2, clustered level 2, fast charging) and the intensity of rollout (EV to charging point ratio). The simulation predicts both the success rate of charging attempts and the additional discomfort when searching for a charging station. Results suggest that return to scale and reciprocal effects in charging infrastructure are considerable, resulting in a lower EV to charging station ratio on the longer term.
The mass adoption of Electric Vehicles (EVs) might raise pressure on the power system, especially during peak hours. Therefore, there is a need for delayed charging. However, to optimize the charging system, the progression of charging from an empty battery to a full battery of the EVs, based on real-world data, needs to be analyzed. Currently, many researchers view this charging profile as a static load and ignore the actual charging behavior during the charging session. However, this study investigates how different factors influence the charging profile of individual EVs based on real-world data of charging sessions in The Netherlands, and thereby enable optimization analysis of EV smart charging schemes.
To achieve emission reduction targets and to improve local air quality of cities, the uptake of Electric Freight Vehicles (EFV) is essential. Knowledge concerning why companies do adopt EFV is lacking. Research about the diffusion of innovations and the market of EFV shows that frontrunner companies with an innovative or early adopting mindset are adopting (or willing to adopt) EFV. Increase in demand of EFV by such companies can help take a step forward towards mass production of EFV and eventually reduction in purchase cost of EFV. The main objective of this paper is to get insights into the decision-making attributes of frontrunner companies. A qualitative approach was used and 14 interviews were conducted among frontrunner companies delivering goods in the city of Amsterdam. Results show that innovators and early adopters are all motivated by socially or environmentally positive effects of EFV. Strategic motives played a role for all companies who already adopted EFV. All companies wanted to adopt EFV but technical limitations, due specialrequirements for the goods transported, are a reason to not adopt EFV. Getting insights into the preferences of frontrunner companies, the (local) authorities can adjust their policy, schemes and sustainability campaigns to attract more companies adopting EFV. Manufacturing companies can use the insights from this research to adapt their vehicle technology to answer needs of the potential customer for faster adoption rate.
In september 2017 startten de lectoraten LEAN-World Class Performance en Automotive Research van de HAN University of Applied Sciences met het onderzoek ‘Werkplaats op Weg’ (cofinanciering door SIA middels het RAAK-MKB subsidieprogramma). Hierin werd de vraag beantwoord: “Wat betekenen alle technologische ontwikkelingen voor de gewenste inrichting van onze onderhoudsprocessen? Wat betekent dit voor acties die we nu en in de nabije toekomst moeten nemen?” De autowerkplaats van de toekomst zal - door innovaties in autotechnologieën, toenemende zorgen over het milieu en klimaat, en een veranderende toekomstvisie op mobiliteit - verschillen van huidige werkplaatsen. Deze ontwikkelingen leidden tot grote onzekerheid bij MKB-ondernemers, met name over de mogelijke effecten op de onderhoudsvraag van voertuigen. Werkplaats op Weg heeft het kennishiaat hieromtrent opgepakt. Op basis van specifieke casussen, interviews en praktijkonderzoeken zijn zes potentiële bedrijfstypes voor het MKB gedefinieerd. Deze zijn gelinkt aan de eerder beschreven technologische en maatschappelijke ontwikkelingen. De relevantste technologische ontwikkelingen die hierin centraal stonden zijn Connected, Autonomous, Shared en Electric Vehicles (CASE; zie figuur 1). De analyse heeft geleid tot concrete en toegankelijke aanbevelingen en online tools. Hiermee kunnen bedrijven binnen de sector hun eigen strategische keuzes maken met betrekking tot het uitvoeren en organiseren van werkzaamheden in hun werkplaats. Tevens is vastgesteld welke consequenties er zijn voor automotive opleidingen. Resultaten van het onderzoek zijn verzameld op de website: www.werkplaatsopweg.nl Figuur 1: Resultaten Werkplaats op Weg Met behulp van de Top-Up willen we onderzoeken hoe ondernemers, onderwijzers en onderzoekers om kunnen gaan met onverwachte, disruptieve veranderingen zoals de Coronacrisis, als aanvulling op de eerdere bevindingen die vooral gericht waren op het omgaan met verwachte technologische innovaties. Gezien de enorme en radicale impact van de huidige coronacrisis, is dit het perfecte moment om de sector extra aandacht en ondersteuning hiertoe aan te bieden.
To reach the European Green Deal by 2050, the target for the road transport sector is set at 30% less CO2 emissions by 2030. Given the fact that heavy-duty commercial vehicles throughout Europe are driven nowadays almost exclusively on fossil fuels it is obvious that transition towards reduced emission targets needs to happen seamlessly by hybridization of the existing fleet, with a continuously increasing share of Zero Emission vehicle units. At present, trailing units such as semitrailers do not possess any form of powertrain, being a missed opportunity. By introduction of electrically driven axles into these units the fuel consumption as well as amount of emissions may be reduced substantially while part of the propulsion forces is being supplied on emission-free basis. Furthermore, the electrification of trailing units enables partial recuperation of kinetic energy while braking. Nevertheless, a number of challenges still exist preventing swift integration of these vehicles to daily operation. One of the dominating ones is the intelligent control of the e-axle so it delivers right amount of propulsion/braking power at the right time without receiving detailed information from the towing vehicle (such as e.g. driver control, engine speed, engine torque, or brake pressure, …etc.). This is required mainly to ensure interoperability of e-Trailers in the fleets, which is a must in the logistics nowadays. Therefore the main mission of CHANGE is to generate a chain of knowledge in developing and implementing data driven AI-based applications enabling SMEs of the Dutch trailer industry to contribute to seamless energetic transition towards zero emission road freight transport. In specific, CHANGE will employ e-Trailers (trailers with electrically driven axle(s) enabling energy recuperation) connected to conventional hauling units as well as trailers for high volume and extreme payload as focal platforms (demonstrators) for deployment of these applications.
Logistics companies struggle to keep their supply chain cost-effective, reliable and sustainable, due to changing demand, increasing competition and growing service requirements. To remain competitive, processes must be efficient with low costs. Of the entire supply chain, the first and last mile logistics may be the most difficult aspect due to low volumes, high waiting and shipping times and complex schedules. These inefficiencies account for up to 40% of total transport costs. Connected Automated Transport (CAT) is a technological development that allows for safer, more efficient and cleaner transport, especially for the first- and last-mile. The Connected Automated Driving Roadmap (ERTRAC) states that CAT can revolutionize the way fleets operate. The CATALYST Project (NWO) already shows the advantages of CAT. SAVED builds on several projects and transforms the challenges and solutions that were identified on a strategic level to a tactical and operational (company) level. Despite the high-tech readiness of CAT, commercial acceptance is lacking due to issues regarding profitable integration into existing logistics processes and infrastructures. In-depth research on automated hub-to-hub freight transport is needed, focusing on ideal vehicle characteristics, logistic control of the vehicles (planning, routing, positioning, battery management), control modes (central, decentralized, hybrid), communication modes (vehicle-to-vehicle, vehicle-to-infrastructure) and automation of loading and unloading, followed by the translation of this knowledge into valid business models. Therefore, SAVED focuses on the following question: “How can automated and collaborative hub-to-hub transport be designed, and what is the impact in terms of People, Planet and Profit (PPP) on the logistics value chain of industrial estates of different sizes, layouts and different traffic situations (mixed/unmixed infrastructure)?“ SAVED results in knowledge of the applicability of CAT and the impact on the logistics value chain of various industrial estates, illustrated by two case studies.
