scholarly journals Enhancing Location Privacy for Electric Vehicles (at the Right time)

2012 ◽  
pp. 397-414 ◽  
Author(s):  
Joseph K. Liu ◽  
Man Ho Au ◽  
Willy Susilo ◽  
Jianying Zhou
Keyword(s):  
Electric Vehicles ◽  
Location Privacy ◽  
The Right

scholarly journals Demographic, Social, Economic, and Regional Factors Affecting the Diffusion of Hybrid Electric Vehicles in Japan

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2130
Author(s):  
Ken’ichi Matsumoto ◽  
Yui Nakamine ◽  
Sunyong Eom ◽  
Hideki Kato
Keyword(s):  
Electric Vehicles ◽  
Urban Areas ◽  
Carbon Dioxide Emissions ◽  
Regional Differences ◽  
Fixed Effects ◽  
Hybrid Electric Vehicles ◽  
Alternative Fuel Vehicles ◽  
Factors Affecting ◽  
Hybrid Electric ◽  
The Right

The transportation sector is a major contributor to carbon dioxide emissions, and the resulting climate change. The diffusion of alternative fuel vehicles, including hybrid electric vehicles (HEV), is an important solution for these issues. This study aimed to evaluate the factors affecting the ownership ratio of HEVs, particularly passenger vehicles, and the regional differences in the purchase of HEVs in Japan. This study performed a fixed-effects regression analysis with panel data for 47 prefectures during the period 2005–2015 to evaluate the factors affecting the HEV ownership ratio and conducted three cluster analyses to investigate the regional differences in diffusion in terms of price categories, body types, and drive systems of HEVs. Some demographic and social factors were found to affect the ownership ratio in Japan, whereas economic factors, including prefecture-level subsidies for purchasing HEVs, were not. Regarding regional differences, prefectures in urban areas with higher income levels tend to purchase more expensive and large-sized HEVs. These results suggest that a strategy to sell the right vehicle to the right person and region is essential for further promoting HEVs in Japan.

scholarly journals Deploying Electric Vehicle Charging Stations Considering Time Cost and Existing Infrastructure

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2436 ◽  
Author(s):  
Yuan Qiao ◽  
Kaisheng Huang ◽  
Johannes Jeub ◽  
Jianan Qian ◽  
Yizhou Song
Keyword(s):  
Electric Vehicles ◽  
Optimization Algorithm ◽  
Central Area ◽  
Time Cost ◽  
Battery Electric Vehicles ◽  
Electric Vehicle Charging ◽  
Service Areas ◽  
Harsh Criticism ◽  
The Right ◽  
Charging Stations

Under the challenge of climate change, fuel-based vehicles have been receiving increasingly harsh criticism. To promote the use of battery electric vehicles (BEVs) as an alternative, many researchers have studied the deployment of BEVs. This paper proposes a new method to choose locations for new BEV charging stations considering drivers’ perceived time cost and the existing infrastructure. We construct probability equations to estimate drivers’ demanding time for charging (and waiting to charge), use the Voronoi diagram to separate the study area (i.e., Shanghai) into service areas, and apply an optimization algorithm to deploy the charging stations in the right locations. The results show that (1) the probability of charging at public charging stations is 39.6%, indicating BEV drivers prefer to charge at home; (2) Shanghai’s central area and two airports have the busiest charging stations, but drivers’ time costs are relatively low; and (3) our optimization algorithm successfully located two new charging stations surrounding the central area, matching with our expectations. This study provides a time-efficient way to decide where to build new charging stations to improve the existing infrastructure.

Developing the "right" breakthrough product/service: an application of the umbrella methodology to electric vehicles - Part B

1999 ◽  
Vol 17 (5) ◽  
pp. 563 ◽  
Author(s):  
Hamid Noori ◽  
Hugh Munro ◽  
Gene Deszca ◽  
Brenda McWilliams
Keyword(s):  
Electric Vehicles ◽  
Product Service ◽  
The Right

scholarly journals Supplier Selection Model of the Lithium-ion Battery using Fuzzy AHP and Analysis of BOCR

2018 ◽  
Vol 1 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Ari Wardayanti ◽  
Roni Zakaria ◽  
Wahyudi Sutopo ◽  
Bendjamin Benny Louhenapessy ◽  
◽  
...  
Keyword(s):  
Lithium Ion Battery ◽  
Electric Vehicles ◽  
Supplier Selection ◽  
Fuzzy Ahp ◽  
Lithium Ion ◽  
Quantitative Model ◽  
The Right ◽  
Hierarchy Process ◽  
Selection Of

Although the demand for the lithium-ion battery for electronic consumers and electric vehicles in Indonesia is high, there is no supplier coming from the local manufacturer. The proper selection of suppliers is required by some lithium-ion battery manufacturers (cells, modules, and packs), and Research and Development (R&D) center of the lithium-ion battery with the consideration not only in benefits and cost but also in opportunities and risks. It is important that experts assist the manufacturers and R&D to procure the lithium-ion (materials and cells), through transparent methods that seek a quantitative model to select the right supplier. The main objective of this study is to propose an analytical approach to select suppliers which incorporate Benefits, Opportunities, Costs and Risks (BOCR) concept that comply with the characteristics of the lithium-ion battery industries. A fuzzy Analytical Hierarchy Process (AHP) model is developed by accommodating the vagueness and inaccuracies of expert elections. The result of this research is development of the model obtained from 2 questionnaires given to the expert. Questionnaire 1 was made for the determination of criteria and sub-criteria, while Questionnaire 2 aims to perform pairwise comparisons of existing criteria and sub-criteria. In the selection of the lithium-ion battery suppliers, there are 11 criteria and 40 sub-criteria which are considered. Those criteria are divided into 4 merits and known for their respective global priorities.

The Power Vehicle with Lateral Collecting Function - Right Direction of Electric Vehicles and Electrified Highway

2013 ◽  
Vol 831 ◽  
pp. 418-422
Author(s):  
Yao Ping Zhang ◽  
Ben Lin Liu
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Power Grid ◽  
Buffer Zone ◽  
Lateral Mode ◽  
The Right ◽  
Better Than

Electrified highway will continuously provide the grid electricity energy directly to power vehicles, also can recharge electricity to the batteries loaded on the running vehicles without stop. Power supplying system of the electrified highway could be laid overhead, sides or ground of the highway. Among the three layouts, the lateral collecting mode where the power supplying system is installed along with the highway buffer zone or fence is better than other two modes. In lateral mode various vehicles with different height could get electricity from the grid directly by the lateral collector extended from one side of the vehicle. The power vehicles with function to gather power from the power grid will lead the electric vehicle industry onto a correct way, and the lateral collecting mode is the prospective and representatives the right direction of power vehicles and electrified highway.

scholarly journals The Location Privacy Protection of Electric Vehicles with Differential Privacy in V2G Networks

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2625 ◽  
Author(s):  
Yuancheng Li ◽  
Pan Zhang ◽  
Yimeng Wang
Keyword(s):  
Electric Vehicles ◽  
Spatial Data ◽  
Privacy Protection ◽  
Smart Grids ◽  
Large Scale ◽  
Location Privacy ◽  
Differential Privacy ◽  
Vehicle To Grid ◽  
Movement Trajectories ◽  
Location Privacy Protection

Vehicle-to-grid (V2G) is an important component of smart grids and plays a significant role in improving grid stability, reducing energy consumption and generating cost. However, while electric vehicles are being charged, it is possible to expose the location and movement trajectories of the electric vehicles, thereby triggering a series of privacy and security issues. In response to this problem, we propose a new quadtree-based spatial decomposition algorithm to protect the location privacy of electric vehicles. First of all, we use a random sampling algorithm, which is based on differential privacy, to obtain enough spatial data to achieve the balance between large-scale spatial data and the amount of noise. Secondly, in order to overcome the shortcomings of using tree height to control Laplacian noise in the quadtree, we use sparse vector technology to control the noise added to the tree nodes. Finally, according to the vehicle-to-grid network structure in the smart grid, we propose a location privacy protection model based on distributed differential privacy technology for EVs in vehicle-to-grid networks. We demonstrate application of the proposed model in real spatial data and show that it can achieve the best effect on the security of the algorithm and the availability of data.

LoPrO: Location Privacy-preserving Online auction scheme for electric vehicles joint bidding and charging

2020 ◽  
Vol 107 ◽  
pp. 394-407 ◽  
Author(s):  
Dou An ◽  
Qingyu Yang ◽  
Wei Yu ◽  
Donghe Li ◽  
Wei Zhao
Keyword(s):  
Electric Vehicles ◽  
Location Privacy ◽  
Privacy Preserving ◽  
Online Auction

scholarly journals Scheduling Charging of Electric Vehicles in a Secured Manner by Emphasizing Cost Minimization Using Blockchain Technology and IPFS

2020 ◽  
Vol 12 (12) ◽  
pp. 5151 ◽  
Author(s):  
Muhammad Umar Javed ◽  
Nadeem Javaid ◽  
Abdulaziz Aldegheishem ◽  
Nabil Alrajeh ◽  
Muhammad Tahir ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Location Privacy ◽  
Cost Minimization ◽  
Weather Conditions ◽  
Time Data ◽  
Conventional Vehicle ◽  
Blockchain Technology ◽  
Vehicle To Vehicle ◽  
Mobile Vehicle ◽  
Shortest Distance

In this work, Electric Vehicles (EVs) are charged using a new and improved charging mechanism called the Mobile-Vehicle-to-Vehicle (M2V) charging strategy. It is further compared with conventional Vehicle-to-Vehicle (V2V) and Grid-to-Vehicle (G2V) charging strategies. In the proposed work, the charging of vehicles is done in a Peer-to-Peer (P2P) manner; the vehicles are charged using Charging Stations (CSs) or Mobile Vehicles (MVs) in the absence of a central entity. CSs are fixed entities situated at certain locations and act as charge suppliers, whereas MVs act as prosumers, which have the capability of charging themselves and also other vehicles. In the proposed system, blockchain technology is used to tackle the issues related with existing systems, such as privacy, security, lack of trust, etc., and also to promote transparency, data immutability, and a tamper-proof nature. Moreover, to store the data related to traffic, roads, and weather conditions, a centralized entity, i.e., Transport System Information Unit (TSIU), is used. It helps in reducing the road congestion and avoids roadside accidents. In the TSIU, an Inter-Planetary File System (IPFS) is used to store the data in a secured manner after removing the data’s redundancy through data filtration. Furthermore, four different types of costs are calculated mathematically, which ultimately contribute towards calculating the total charging cost. The shortest distance between a vehicle and the charging entities is calculated using the Great-Circle Distance formula. Moving on, both the time taken to traverse this shortest distance and the time to charge the vehicles are calculated using real-time data of four EVs. Location privacy is also proposed in this work to provide privacy to vehicle users. The power flow and the related energy losses for the above-mentioned charging strategies are also discussed in this work. An incentive provisioning mechanism is also proposed on the basis of timely delivery of credible messages, which further promotes users’ participation. In the end, simulations are performed and results are obtained that prove the efficiency of the proposed work, as compared to conventional techniques, in minimizing the EVs’ charging cost, time, and distance.

scholarly journals Energy Management Strategies for Hybrid Electric Vehicles: Review, Classification, Comparison, and Outlook

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3352 ◽  
Author(s):  
Fengqi Zhang ◽  
Lihua Wang ◽  
Serdar Coskun ◽  
Hui Pang ◽  
Yahui Cui ◽  
...  
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Power Distribution ◽  
Hybrid Electric Vehicles ◽  
Management Strategies ◽  
Unified Framework ◽  
Advantages And Disadvantages ◽  
Conflicting Objectives ◽  
Hybrid Electric ◽  
The Right

Hybrid Electric Vehicles (HEVs) have been proven to be a promising solution to environmental pollution and fuel savings. The benefit of the solution is generally realized as the amount of fuel consumption saved, which by itself represents a challenge to develop the right energy management strategies (EMSs) for HEVs. Moreover, meeting the design requirements are essential for optimal power distribution at the price of conflicting objectives. To this end, a significant number of EMSs have been proposed in the literature, which require a categorization method to better classify the design and control contributions, with an emphasis on fuel economy, providing power demand, and real-time applicability. The presented review targets two main headlines: (a) offline EMSs wherein global optimization-based EMSs and rule-based EMSs are presented; and (b) online EMSs, under which instantaneous optimization-based EMSs, predictive EMSs, and learning-based EMSs are put forward. Numerous methods are introduced, given the main focus on the presented scheme, and the basic principle of each approach is elaborated and compared along with its advantages and disadvantages in all aspects. In this sequel, a comprehensive literature review is provided. Finally, research gaps requiring more attention are identified and future important trends are discussed from different perspectives. The main contributions of this work are twofold. Firstly, state-of-the-art methods are introduced under a unified framework for the first time, with an extensive overview of existing EMSs for HEVs. Secondly, this paper aims to guide researchers and scholars to better choose the right EMS method to fill in the gaps for the development of future-generation HEVs.

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