产业链视角下充电基础设施商业模式研究

充电基础设施市场不断扩张,使原有商业模式无法适用,企业想要获得市场竞争力,需对商业模式进行创新发展.本文通过梳理充电基础设施产业链及产业链中各利益相关者之间的关系,分析充电基础设施以各利益相关者为主导的运营模式,由此设计集"车-桩-网-源"为一体的充电基础设施建设开放式服务平台的商业模式,该商业模式从B2C自主、B2C...     

The role of charging and refuelling infrastructure in supporting zero-emission vehicle sales

Widespread uptake of battery electric, plug-in hybrid, and hydrogen fuel-cell vehicles (collectively zero-emissions vehicles or ZEVs) could help many regions achieve deep greenhouse gas mitigation goals. Using the case of Canada, this study investigates the extent to which increasing ZEV charging and refuelling availability may boost ZEV sales relative to other ZEV-supportive policies. We adapt a version of the Respondent-based Preferences and Constraints (REPAC) model using 2017 survey data from 1884 Canadian new vehicle-buyers to simulate the sales impacts of increasing electric vehicle charging access at home, work, public destinations, and on highways, as well as increasing hydrogen refuelling station access. REPAC is built from a stated preference choice model and represents constraints in supply and consumer awareness, as well as dynamics in ZEV policy out to 2030. Results suggest that new ZEV market share from 2020 to 2030 does not substantially benefit from increased infrastructure. Even when electric charging and hydrogen refuelling access are simulated to reach “universally” available levels by 2030, ZEV sales do not rise by more than 1.5 percentage points above the baseline trajectory. On the other hand, REPAC simulates ZEV market share rising as high as 30% by 2030 with strong ZEV-supportive policies, even without the addition of charging or refuelling infrastructure. These findings stem from low consumer valuation of infrastructure found in the stated preference model. Results suggest that achieving ambitious ZEV sale targets requires a comprehensive suite of policies beyond a focus on charging and refueling infrastructure.     

新能源汽车消费者充电行为习惯及配套设施使用现状分析

文章主要研究新能源汽车消费者充电习惯和行为特征,并探索不同城市级别、不同意识形态和不同充电设施消费者充电行为差异性。通过分析和对比,挖掘不同新能源汽车消费者充电特点,以及在充电过程中的主要困难和不便,一方面为新能源汽车企业了解消费者充电行为提供参考,另一方面为充电设施的完善和改进提供方向。此外,在分析消费者充电现状的同时,还进一步了解其对充电配套设施的需求和期望,为未来充电设施布局指明方向。     

Shared autonomous electric vehicle service performance: Assessing the impact of charging infrastructure

Shared autonomous vehicles (SAVs) are the next major evolution in urban mobility. This technology has attracted much interest of car manufacturers aiming at playing a role as transportation network companies (TNCs) and carsharing agencies in order to gain benefits per kilometer and per ride. It is predicted that the majority of future SAVs would most probably be electric. It is therefore important to understand how limited vehicle range and the configuration of charging infrastructure will affect the performance of shared autonomous electric vehicle (SAEV) services. In this study, we aim to explore the impacts of charging station placement, charging types (including normal and rapid charging, and battery swapping), and vehicle battery capacities on service efficiency. We perform an agent-based simulation of SAEVs across the Rouen Normandie metropolitan area in France. The simulation process features impact assessment by considering dynamic demand responsive to the network and traffic.Research results suggest that the performance of SAEVs is strongly correlated with the charging infrastructure. Importantly, faster charging infrastructure and placement of charging locations according to minimized distances between demand hubs and charging stations result in a higher performance. Further analysis indicates the importance of dispersing charging stations across the service area and its impacts on service effectiveness. The results also underline that SAEV battery capacity has to be selected carefully such that to avoid the overlaps between demand and charging peak times. Finally, the simulation results show that the performance indicators of SAEV service are significantly improved by providing battery swapping infrastructure.     

CFCS-1型锂离子电池充放电测试装置的研制

本文介绍了一种以单片机作为控制核心的新型智能锂离子电池充放电测试装置的研制方法。该装置不仅能提供完全独立的充放电测试通道,还能对锂离子电池在充放电过程中提供过流、过压、欠压故障报警。由于采用了CAN总线技术及模块化设计,该装置不但降低了成本,还提高了实时性、可靠性和互换性。     

Optimal locations of electric public charging stations using real world vehicle travel patterns

We propose an optimization model based on vehicle travel patterns to capture public charging demand and select the locations of public charging stations to maximize the amount of vehicle-miles-traveled (VMT) being electrified. The formulated model is applied to Beijing, China as a case study using vehicle trajectory data of 11,880 taxis over a period of three weeks. The mathematical problem is formulated in GAMS modeling environment and Cplex optimizer is used to find the optimal solutions. Formulating mathematical model properly, input data transformation, and Cplex option adjustment are considered for accommodating large-scale data. We show that, compared to the 40 existing public charging stations, the 40 optimal ones selected by the model can increase electrified fleet VMT by 59% and 88% for slow and fast charging, respectively. Charging demand for the taxi fleet concentrates in the inner city. When the total number of charging stations increase, the locations of the optimal stations expand outward from the inner city. While more charging stations increase the electrified fleet VMT, the marginal gain diminishes quickly regardless of charging speed.     

Deployment of stationary and dynamic charging infrastructure for electric vehicles along traffic corridors

As charging-while-driving (CWD) technology advances, charging lanes can be deployed in the near future to charge electric vehicles (EVs) while in motion. Since charging lanes will be costly to deploy, this paper investigates the deployment of two types of charging facilities, namely charging lanes and charging stations, along a long traffic corridor to explore the competitiveness of charging lanes. Given the charging infrastructure supply, i.e., the number of charging stations, the number of chargers installed at each station, the length of charging lanes, and the charging prices at charging stations and lanes, we analyze the charging-facility-choice equilibrium of EVs. We then discuss the optimal deployment of charging infrastructure considering either the public or private provision. In the former, a government agency builds and operates both charging lanes and stations to minimize social cost, while in the latter, charging lanes and stations are assumed to be built and operated by two competing private companies to maximize their own profits. Numerical experiments based on currently available empirical data suggest that charging lanes are competitive in both cases for attracting drivers and generating revenue.     

Energy impact evaluation for eco-routing and charging of autonomous electric vehicle fleet: Ambient temperature consideration

This paper studies the heterogeneous energy cost and charging demand impact of autonomous electric vehicle (EV) fleet under different ambient temperature. A data-driven method is introduced to formulate a two-dimensional grid stochastic energy consumption model for electric vehicles. The energy consumption model aids in analyzing EV energy cost and describing uncertainties under variable average vehicle trip speed and ambient temperature conditions. An integrated eco-routing and optimal charging decision making framework is designed to improve the capability of autonomous EV’s trip level energy management in a shared fleet. The decision making process helps to find minimum energy cost routes with consideration of charging strategies and travel time requirements. By taking advantage of derived models and technologies, comprehensive case studies are performed on a data-driven simulated transportation network in New York City. Detailed results show us the heterogeneous energy impact and charging demand under different ambient temperature. By giving the same travel demand and charging station information, under the low and high ambient temperature within each month, there exist more than 20% difference of overall energy cost and 60% difference of charging demand. All studies will help to construct sustainable infrastructure for autonomous EV fleet trip level energy management in real world applications.     

Impact of convenient away-from-home charging infrastructure

This work uses market analysis and simulation to explore the potential impact of workplace and similarly convenient away-from-home charging infrastructure (CAFHCI) in reducing US light duty vehicle (LDV) petroleum use and greenhouse gas emissions. The ParaChoice model simulates the evolution of LDV sales, fuel use, and emissions through 2050, considering consumer responses to different options of electric range extension made available through CAFHCI, fraction of the population with access, and delay in infrastructure implementation. Results indicate that providing a greater fraction of the population access to CAFHCI at level 1 charging rates for a full workday (∼16–20 miles of range extension) may lead to more petroleum use reduction than providing level 2 charging to a lesser fraction. This result holds even considering the fraction of the population without at-home charging. 2050 battery electric vehicle sales increase 40% (85%) if the entire population is guaranteed daily access to one full workday of level 1 CAFHCI (half a workday of level 2, ∼80 miles of range extension). Plug-in hybrid sales increase when CAFHCI enables range extension below 20–40 miles/day, most significantly in households without at-home charging capability. Faster CAFHCI may decrease plug-in hybrid sales as less expensive BEVs become attractive to a greater fraction of the market.