scholarly journals Estimation of the Size of the Battery for Hybrid Electric Trolley Busses Using Backward Quasi-Static Modelling

Proceedings ◽  
2018 ◽  
Vol 2 (23) ◽  
pp. 1499
Author(s):  
Abhishek Singh Tomar ◽  
Bram Veenhuizen ◽  
Lejo Buning ◽  
Ben Pyman
Keyword(s):  
Scenario Analysis ◽  
Range Extension ◽  
Charging Infrastructure ◽  
Grid Network ◽  
Battery Capacity ◽  
Local Emission ◽  
Static Modeling ◽  
Driving Range ◽  
Static Modelling ◽  
The City

The city of Arnhem is known for its trolley busses, which operates in a network of over-head grid lines, leading to zero local emission. However, extending the driving range of the trolley busses beyond the over-head grid network is technically challenging and economically demanding due to the infrastructure requirements. This led to their participation in EUREGIO project e-Bus 2020 IMC. The aim of the project is to develop, design and optimize a hybrid driveline for trolley busses using an additional traction battery. Using the over-head grid network for In Motion Charging (IMC), eliminates the need for a separate charging infrastructure needed for regular electric busses. This paper presents a backward quasi-static modeling approach to estimate the battery capacity for the required range extension. The viability of the battery is verified using a scenario analysis.

scholarly journals Consumer Preferences for Electric Vehicle Charging Infrastructure Based on the Text Mining Method

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4598
Author(s):  
Yuan-Yuan Wang ◽  
Yuan-Ying Chi ◽  
Jin-Hua Xu ◽  
Jia-Lin Li
Keyword(s):  
Language Processing ◽  
Consumer Preferences ◽  
National Policy ◽  
High Energy ◽  
Policy Support ◽  
Charging Infrastructure ◽  
Electric Vehicle Charging ◽  
Driving Range ◽  
Second Tier ◽  
Development Levels

The construction of charging infrastructure has a positive effect on promoting the diffusion of new energy vehicles (NEVs). This study uses natural language processing (NLP) technology to explore consumer preferences for charging infrastructure from consumer comments posted on public social media. The findings show that consumers in first-tier cities pay more attention to charging infrastructure, and the number of comments accounted for 36% of the total. In all comments, consumers are most concerned about charging issues, national policy support, driving range, and installation of private charging piles. Among the charging modes of charging piles, direct current (DC) fast charging is more popular with consumers. The inability to find public charging piles in time to replenish power during travel or high energy consumption caused by air conditioning is the main reason for consumers’ range anxiety. Increasing battery performance, improving charging convenience, and construction of battery swap station are the main ways consumers prefer to increase driving range. Consumers’ preference for charging at home is the main reason for their high attention to the installation of private charging piles. However, the lack of fixed parking spaces and community properties have become the main obstacles to the installation of private charging piles. In addition, consumers in cities with different development levels pay different amounts of attention to each topic of charging infrastructure. Consumers in second-tier and above cities are most concerned about charging issues. Consumers in third-tier and above cities pay significantly more attention to the installation of private charging piles than consumers in fourth-tier and fifth-tier cities. Consumers in each city have almost the same amount of attention to driving range.

scholarly journals Interdisciplinary Analysis of Social Acceptance Regarding Electric Vehicles with a Focus on Charging Infrastructure and Driving Range in Germany

2021 ◽  
Vol 12 (1) ◽  
pp. 25
Author(s):  
Amelie Burkert ◽  
Heiko Fechtner ◽  
Benedikt Schmuelling
Keyword(s):  
Value Chain ◽  
Social Acceptance ◽  
Electric Mobility ◽  
Transport Sector ◽  
Special Focus ◽  
Full Potential ◽  
Negative Effects ◽  
Resource Saving ◽  
Charging Infrastructure ◽  
Driving Range

A variety of measures are currently being taken on both the national and international levels in order to mitigate the negative effects of climate change. The promotion of electric mobility is one such measure for the transport sector. As a key component in a more environmentally-friendly, resource-saving, and efficient transport sector, electric mobility promises to create better sustainability. Several challenges still need to be met to exploit its full potential. This requires adapting the car technology, the value chain of vehicles, loads on the electricity network, the power generation for the drive, traffic, and charging infrastructure. The challenges to this endeavor are not only technical in nature, but they also include social acceptance, concerns, and economic, as well as ecological, aspects. This paper seeks to discuss and elucidate these problems, giving special focus to the issues of driving range, phenomenon of range anxiety, charging time, and complexity of the charging infrastructure in Germany. Finally, the development of social acceptance in Germany from 2011 to 2020 is investigated.

scholarly journals Long Term Energy Transition Scenario Analysis for the City of Donostia

Proceedings ◽  
2018 ◽  
Vol 1 (7) ◽  
pp. 644
Author(s):  
Eneko Arrizabalaga ◽  
Patxi Hernandez ◽  
Luis del Portillo-Valdés
Keyword(s):  
Scenario Analysis ◽  
Energy Transition ◽  
Term Energy ◽  
The City ◽  
Transition Scenario

Swarm Intelligence-Based Optimization for PHEV Charging Stations

2015 ◽  
pp. 374-405 ◽  
Author(s):  
Imran Rahman ◽  
Pandian Vasant ◽  
Balbir Singh Mahinder Singh ◽  
M. Abdullah-Al-Wadud
Keyword(s):  
Hybrid Electric Vehicle ◽  
Performance Indicator ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Computation Time ◽  
Charging Infrastructure ◽  
Charging Time ◽  
Battery Capacity ◽  
Hybrid Electric ◽  
Charging Stations

In this chapter, Gravitational Search Algorithm (GSA) and Particle Swarm Optimization (PSO) technique were applied for intelligent allocation of energy to the Plug-in Hybrid Electric Vehicles (PHEVs). Considering constraints such as energy price, remaining battery capacity, and remaining charging time, they optimized the State-of-Charge (SoC), a key performance indicator in hybrid electric vehicle for the betterment of charging infrastructure. Simulation results obtained for maximizing the highly non-linear objective function evaluates the performance of both techniques in terms of global best fitness and computation time.

scholarly journals Charging Schedule for Load Peak Minimization on Large-Scale Electric Bus Depots

2019 ◽  
Vol 9 (9) ◽  
pp. 1748 ◽  
Author(s):  
Amra Jahic ◽  
Mina Eskander ◽  
Detlef Schulz
Keyword(s):  
Public Transportation ◽  
Large Scale ◽  
Peak Load ◽  
Load Profile ◽  
Charging Infrastructure ◽  
Scheduling System ◽  
Electric Bus ◽  
Local Grid ◽  
Load Peak ◽  
The City

The city of Hamburg has decided to electrify its bus fleets. The two public transportation companies in this city expect to operate up to 1500 buses by 2030. In order to accomplish this ambitious goal, both companies need to build an appropriate charging infrastructure. They have both decided to implement the centralized depot charging concept. Buses can therefore charge only at the depot and do not have the possibility for opportunity charging at intermediate stations. The load profile of such a bus depot is highly dependent on the charging schedule of buses. Without an intelligent scheduling system, the buses charge on demand as soon as they arrive to the depot. This can lead to an unevenly distributed load profile with high load peaks, which is problematic for the local grid as well as for the equipment dimensioning at the depot. Charging scheduling on large-scale bus depots is a relatively new and poorly researched topic. This paper addresses the issue and proposes two algorithms for charging scheduling on large-scale bus depots with the goal to minimize the peak load. The schedules created with the proposed algorithms were both tested and validated in the Bus Depot Simulator, a cosimulation platform used for bus depot simulations.

Sign in / Sign up

Export Citation Format

Share Document