scholarly journals Evaluating On-Road Emissions Impacts of HEVs, PHEVs and EVs: An Integrated Modeling Framework

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Kejia Hu ◽  
Jianyou Zhao ◽  
Yuche Chen ◽  
L.D. White
Keyword(s):  
Electric Vehicles ◽  
Consumer Choice ◽  
Choice Model ◽  
Government Policies ◽  
Harris County ◽  
Road Transportation ◽  
Modeling Framework ◽  
Transportation Emissions ◽  
Carbon Dioxide Co2

This paper develops a framework to evaluate HEVs, PHEVs and EVs on-road emissions impact, by integrating endogenous vehicle consumer choice model and MOVES-based regional emission transportation model. A case study based on Harris County, Texas data is implemented to examine the on-road emissions under different market penetrations (due to different future energy price) and government policies. The results show different on-road transportation emissions level for Carbon Dioxide (CO2), Carbon Monoxide (CO), Nitrogen Oxide (NOx) and Total Hydrocarbon (THC). In addition, cost effectiveness of reducing on-road emissions by extending tax credit for plug-in electric vehicles (PEV) is calculated and reported. 

scholarly journals Evaluating On-Road Emissions Impacts of HEVs, PHEVs and EVs: An Integrated Modeling Framework

2018 ◽  
Author(s):  
Kejia Hu ◽  
Jianyou Zhao ◽  
Yuche Chen ◽  
L.D. White
Keyword(s):  
Electric Vehicles ◽  
Consumer Choice ◽  
Choice Model ◽  
Government Policies ◽  
Harris County ◽  
Road Transportation ◽  
Modeling Framework ◽  
Transportation Emissions ◽  
Carbon Dioxide Co2

This paper develops a framework to evaluate HEVs, PHEVs and EVs on-road emissions impact, by integrating endogenous vehicle consumer choice model and MOVES-based regional emission transportation model. A case study based on Harris County, Texas data is implemented to examine the on-road emissions under different market penetrations (due to different future energy price) and government policies. The results show different on-road transportation emissions level for Carbon Dioxide (CO2), Carbon Monoxide (CO), Nitrogen Oxide (NOx) and Total Hydrocarbon (THC). In addition, cost effectiveness of reducing on-road emissions by extending tax credit for plug-in electric vehicles (PEV) is calculated and reported. 

A Framework for Choice Modeling in Usage Context-Based Design

2010 ◽  
Author(s):  
Lin He ◽  
Christopher Hoyle ◽  
Wei Chen ◽  
Jiliang Wang ◽  
Bernard Yannou
Keyword(s):  
Data Collection ◽  
Product Design ◽  
Consumer Choice ◽  
Choice Model ◽  
Consumer Preferences ◽  
Choice Modeling ◽  
Product Performance ◽  
Choice Data ◽  
Modeling Framework ◽  
Usage Context

Usage Context-Based Design (UCBD) is an area of growing interest within the design community. A framework and a step-by-step procedure for implementing consumer choice modeling in UCBD are presented in this work. To implement the proposed approach, methods for common usage identification, data collection, linking performance with usage context, and choice model estimation are developed. For data collection, a method of try-it-out choice experiments is presented. This method is necessary to account for the different choices respondents make conditional on the given usage context, which allows us to examine the influence of product design, customer profile, usage context attributes, and their interactions, on the choice process. Methods of data analysis are used to understand the collected choice data, as well as to understand clusters of similar customers and similar usage contexts. The choice modeling framework, which considers the influence of usage context on both the product performance, choice set and the consumer preferences, is presented as the key element of a quantitative usage context-based design process. In this framework, product performance is modeled as a function of both the product design and the usage context. Additionally, usage context enters into an individual customer’s utility function directly to capture its influence on product preferences. The entire process is illustrated with a case study of the design of a jigsaw.

scholarly journals Beijing’s Peak Car Transition: Hope for Emerging Cities in the 1.5 °C Agenda

2018 ◽  
Vol 3 (2) ◽  
pp. 82-93 ◽  
Author(s):  
Yuan Gao ◽  
Peter Newman
Keyword(s):  
Electric Vehicles ◽  
Government Policies ◽  
Car Ownership ◽  
Traffic Demand ◽  
Car Use ◽  
The Past ◽  
Peak Car ◽  
Private Car ◽  
Per Capita

Peak car has happened in most developed cities, but for the 1.5 °C agenda the world also needs emerging cities to go through this transition. Data on Beijing shows that it has reached peak car over the past decade. Evidence is provided for peak car in Beijing from traffic supply (freeway length per capita and parking bays per private car) and traffic demand (private car ownership, automobile modal split, and Vehicle Kilometres Travelled per capita). Most importantly the data show Beijing has reduced car use absolutely whilst its GDP has continued to grow. Significant growth in electric vehicles and bikes is also happening. Beijing’s transition is explained in terms of changing government policies and emerging cultural trends, with a focus on urban fabrics theory. The implications for other emerging cities are developed out of this case study. Beijing’s on-going issues with the car and oil will remain a challenge but the first important transition is well underway.

An Empirical Study of Store Choice Model: An Endogenous Construct

2014 ◽  
Vol 4 (2) ◽  
Author(s):  
Prof. Amit Shrivastava ◽  
Prof. Sushil Kumar Pare ◽  
Prof (Dr) Saumya Singh
Keyword(s):  
Empirical Research ◽  
Consumer Choice ◽  
Choice Model ◽  
Social Science Research ◽  
Product Category ◽  
Science Research ◽  
Consumer Decision Making ◽  
Store Choice ◽  
Store Attributes ◽  
Patronage Intention

Inadequate is the empirical research on store choice model in view of retail store attributes with endogenous construct of store patronage intention of consumer. Conventional wisdom and social science research-based insights for underpinning the design of store environment established elements such as music, scent, crowding and physical attractiveness of the store. Earlier empirical findings lack on key anterior, which include consumers’ time and effort as well as the psychological costs such as convenient, economical, risk mitigated shopping experience. The premise on which overall effects in our model rests, is that store attributes influence consumers' cognitive process and develop perceptual framework of store choice criteria — namely, convenience, reputation of outlet, branded merchandise (mediated through perceived quality). This research presents a formal test of the linear regression equation model in the context of store choice behaviour, involving one product category. The present paper explores these attributes and their affect on consumer from different socio-economic classes, willingness to purchase and to patronize if these factors are modified. Questioning the earlier conclusions that all attributes aforementioned are equally important in consumer decision making, the current results indicate that consumers place differential significance on each attribute, and the level of significance placed on each attribute varies with different socio economic class. These findings are significantly important to the retail industry as they identify the critical attributes responsible for building consumer choice and patronage among different socio economy classes. This model also paves way for another premise of empirical research, that shoppers might develop category-wise store choice or patronage behaviour model.

scholarly journals Electric Vehicle Integration into Road Transportation, Intelligent Transportation, and Electric Power Systems: An Abu Dhabi Case Study

Smart Cities ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 1039-1057
Author(s):  
Amro M. Farid ◽  
Asha Viswanath ◽  
Reem Al-Junaibi ◽  
Deema Allan ◽  
Thomas J. T. Van der Van der Wardt
Keyword(s):  
Electric Power ◽  
Intelligent Transportation ◽  
Energy System ◽  
Transportation System ◽  
Electric Power System ◽  
Abu Dhabi ◽  
Road Transportation ◽  
Unit Distance ◽  
The Impact

Recently, electric vehicles (EV) have gained much attention as a potential enabling technology to support CO2 emissions reduction targets. Relative to their internal combustion vehicle counterparts, EVs consume less energy per unit distance, and add the benefit of not emitting any carbon dioxide in operation and instead shift their emissions to the existing local fleet of power generation. However, the true success of EVs depends on their successful integration with the supporting infrastructure systems. Building upon the recently published methodology for the same purpose, this paper presents a “systems-of-systems” case study assessing the impacts of EVs on these three systems in the context of Abu Dhabi. For the physical transportation system, a microscopic discrete-time traffic operations simulator is used to predict the kinematic state of the EV fleet over the duration of one day. For the impact on the intelligent transportation system (ITS), the integration of EVs into Abu Dhabi is studied using a multi-domain matrix (MDM) of the Abu Dhabi Department of Transportation ITS. Finally, for the impact on the electric power system, the EV traffic flow patterns from the CMS are used to calculate the timing and magnitude of charging loads. The paper concludes with the need for an intelligent transportation-energy system (ITES) which would coordinate traffic and energy management functionality.

scholarly journals Optimized Strategic Planning of Future Norwegian Low-Voltage Networks with a Genetic Algorithm Applying Empirical Electric Vehicle Charging Data

Electricity ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 91-109
Author(s):  
Julian Wruk ◽  
Kevin Cibis ◽  
Matthias Resch ◽  
Hanne Sæle ◽  
Markus Zdrallek
Keyword(s):  
Genetic Algorithm ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Low Voltage ◽  
Network Planning ◽  
Voltage Regulation ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
The Impact

This article outlines methods to facilitate the assessment of the impact of electric vehicle charging on distribution networks at planning stage and applies them to a case study. As network planning is becoming a more complex task, an approach to automated network planning that yields the optimal reinforcement strategy is outlined. Different reinforcement measures are weighted against each other in terms of technical feasibility and costs by applying a genetic algorithm. Traditional reinforcements as well as novel solutions including voltage regulation are considered. To account for electric vehicle charging, a method to determine the uptake in equivalent load is presented. For this, measured data of households and statistical data of electric vehicles are combined in a stochastic analysis to determine the simultaneity factors of household load including electric vehicle charging. The developed methods are applied to an exemplary case study with Norwegian low-voltage networks. Different penetration rates of electric vehicles on a development path until 2040 are considered.

scholarly journals On the Investigation of Energy Efficient Torque Distribution Strategies through a Comprehensive Powertrain Model

2021 ◽  
Vol 13 (8) ◽  
pp. 4549
Author(s):  
Sara Salamone ◽  
Basilio Lenzo ◽  
Giovanni Lutzemberger ◽  
Francesco Bucchi ◽  
Luca Sani
Keyword(s):  
Energy Storage ◽  
Electric Vehicles ◽  
Energy Efficient ◽  
Storage System ◽  
Energy Storage System ◽  
Torque Distribution ◽  
Driving Cycles ◽  
Energy Models ◽  
Battery State Of Charge

In electric vehicles with multiple motors, the torque at each wheel can be controlled independently, offering significant opportunities for enhancing vehicle dynamics behaviour and system efficiency. This paper investigates energy efficient torque distribution strategies for improving the operational efficiency of electric vehicles with multiple motors. The proposed strategies are based on the minimisation of power losses, considering the powertrain efficiency characteristics, and are easily implementable in real-time. A longitudinal dynamics vehicle model is developed in Simulink/Simscape environment, including energy models for the electrical machines, the converter, and the energy storage system. The energy efficient torque distribution strategies are compared with simple distribution schemes under different standardised driving cycles. The effect of the different strategies on the powertrain elements, such as the electric machine and the energy storage system, are analysed. Simulation results show that the optimal torque distribution strategies provide a reduction in energy consumption of up to 5.5% for the case-study vehicle compared to simple distribution strategies, also benefiting the battery state of charge.

A review on powertrain subsystems and charging technology in battery electric vehicles: Current and future trends

2021 ◽  
pp. 095440702110259
Author(s):  
Kunal Wagh ◽  
Pankaj Dhatrak
Keyword(s):  
Electric Vehicles ◽  
Combustion Engine ◽  
Future Research ◽  
Future Trends ◽  
Road Transportation ◽  
Market Prices ◽  
Local Pollution ◽  
Battery Electric Vehicles ◽  
Global Emission ◽  
Battery Technology

The transport industry is a major contributor to both local pollution and greenhouse gas emissions (GHGs). The key challenge today is to mitigate the adverse impacts on the environment caused by road transportation. The volatile market prices and diminishing supplies of fuel have led to an unprecedented interest in battery electric vehicles (BEVs). In addition, improvements in motor efficiencies and significant advances in battery technology have made it easier for BEVs to compete with internal combustion engine (ICE) vehicles. This paper describes and assesses the latest technologies in different elements of the BEV: powertrain architectures, propulsion and regeneration systems, energy storage systems and charging techniques. The current and future trends of these technologies have been reviewed in detail. Finally, the key issue of electric vehicle component recycling (battery, motor and power electronics) has been discussed. Global emission regulations are pushing the industry towards zero or ultra-low emission vehicles. Thus, by 2025, most cars must have a considerable level of powertrain electrification. As the market share of electric vehicles increases, clear trends have emerged in the development of powertrain systems. However, some significant barriers must be overcome before appreciable market penetration can be achieved. The objective of the current study is to review and provide a complete picture of the current BEV technology and a framework to assist future research in the sector.

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