Open synthetic data on travel and charging demand of battery electric cars: An agent-based simulation on three charging behavior archetypes

<strong>Background</strong> Battery electric vehicles (BEVs) are crucial for a sustainable transportation system. As more people adopt BEVs, it becomes increasingly important to accurately assess the demand for charging infrastructure. However, much of the current research on charging infrastructure relies on outdated assumptions, such as the assumption that all BEV owners have access to home chargers and the "Liquid-fuel" mental model. To address this issue, we simulate the travel and charging demand on three charging behavior archetypes. We use a large synthetic population of Sweden, including detailed individual characteristics, such as dwelling types (detached house vs. apartment) and activity plans (for an average weekday). This data repository aims to provide the BEV simulation's input, assumptions, and output so that other studies can use them to study sizing and location design of charging infrastructure, grid impact, etc. A journal paper published in Transportation Research Part D: Transport and Environment details the method to create the data (particularly Section 2.2 BEV simulation). https://doi.org/10.1016/j.trd.2023.103645 <strong>Methodology</strong> This data product is centered on the 1.7 million inhabitants of the Västra Götaland (VG) region, which includes the second largest city in Sweden, Gothenburg. We specifically simulated 284,000 car agents who live in VG, representing 35% of all car users and 18% of the total population in the region. They spend their simulation day (representing an average weekday) in a variety of locations throughout Sweden. This open data repository contains the core model inputs and outputs. The numbers in parentheses correspond to the data sets. We use individual agents' activity plans (1) and travel trajectories from MATSim simulation for the BEV simulation (2), in which we consider overnight charger access (3), car fleet composition referencing the current private car fleet in Sweden (4), and Swedish road network with slope information (5) with realistic BEV charging &amp; discharging dynamics. For the BEV simulation, we tested ten scenarios of charging behavior archetypes and fast charging powers (6). The output includes the time history of travel trajectories and charging of the simulated BEVs across the different scenarios (7). <strong>Data description</strong> The current data product covers seven data files. <strong>(1) Agents' experienced activity plans</strong> File name: 1_activity_plans.csv <strong>Column</strong> <strong>Description</strong> <strong>Data type</strong> <strong>Unit</strong> person Agent ID Integer - act_id Activity index of each agent Integer - deso Zone code of Demographic statistical areas (DeSO)¹ String - POINT_X Coordinate X of activity location (SWEREF99TM) Float meter POINT_Y Coordinate Y of activity location (SWEREF99TM) Float meter act_purpose Activity purpose (work, home, other) String - mode Transport mode to reach the activity location (car) String - dep_time Departure time in decimal hour (0-23.99) Float hour trav_time Travel time to reach the activity location String hour:minute:second trav_time_min Travel time in decimal minute Float minute speed Travel speed to reach the activity location Float km/h distance Travel distance between the origin and the destination Float km act_start Start time of activity in minute (0-1439) Integer minute act_time Activity duration in decimal minute Float minute act_end End time of activity in decimal hour (0-23.99) Float hour score Utility score of the simulation day given by MATSim Float - 1 https://www.scb.se/vara-tjanster/oppna-data/oppna-geodata/deso--demografiska-statistikomraden/ <strong>(2) Travel trajectories</strong> File name: 2_input_zip Produced by MATSim simulation, the zip folder contains ten files (events_batch_X.csv.gz, X=1, 2, …, 10) of input events for the BEV simulation. They are the moving trajectories of the car agents in their simulation days. <strong>Column</strong> <strong>Description</strong> <strong>Data type</strong> <strong>Unit</strong> time Time in second in a simulation day (0-86399) Integer Second type Event type defined by MATSim simulation² String - person Agent ID Integer - link Nearest road link consistent with (5) String - vehicle Vehicle ID identical to person Integer - ²One typical episode of MATSim simulation events: Activity ends (actend) -&gt; Agent’s vehicle enters traffic (vehicle enters traffic) -&gt; Agent’s vehicle moves from previous road segment to its next connected one (left link) -&gt; Agent’s vehicle leaves traffic for activity (vehicle leaves traffic) -&gt; Activity starts (actstart) <strong>(3) Overnight charger access</strong> File name: 3_home_charger_access.csv <strong>Column</strong> <strong>Description</strong> <strong>Data type</strong> <strong>Unit</strong> person Agent ID Integer - home_charger Whether an agent has access to a home garage charger/living in a detached house (0=no, 1=yes) Integer - <strong>(4) Car fleet composition</strong> File name: 4_car_fleet.csv <strong>Column</strong> <strong>Description</strong> <strong>Data type</strong> <strong>Unit</strong> person Agent ID Integer - income_class Income group (0=None, 1=below 180K, 2=180K-300K, 3=300K-420K, 4=above 420K) Integer - car Car model class (B=40 kWh, C=60 kWh, D=100 kWh) String - (<strong>5) Road network with slope information</strong> File name: 5_road_network_with_slope.shp (5 files in total) Column Description Data type Unit length The length of road link Float meter freespeed Free speed Float km/h capacity Number of vehicles Integer - permlanes Number of lanes Integer - oneway Whether the segment is one-way (0=no, 1=yes) Integer - modes Transport mode (car) String - link_id Link ID String - from_node Start node of the link String - to_node End node of the link String - count Aggregated traffic (number of cars travelled per day) Integer - slope Slope in percent from -6% to 6% Float - geometry LINESTRING (SWEREF99TM) geometry meter <strong>(6) Simulation scenarios specifying the parameter sets</strong> File name: 6_scenarios.txt <strong>Parameter set</strong> <strong>(paraset)</strong> <strong>Strategy 1</strong> <strong>Strategy 2</strong> <strong>Strategy 3</strong> <strong>Fast charging power (kW)</strong> <strong>Minimum parking time for charging (min)</strong> <strong>Intermediate charging power (kW)</strong> 0 0.2 0.2 0.9 150 5 22 1 0.2 0.2 0.9 50 5 22 2 0.3 0.3 0.9 150 5 22 3 0.3 0.3 0.9 50 5 22 <strong>(7) Time history of travel trajectories and charging of the simulated BEVs</strong> File name: 7_output.zip Produced by the BEV simulation, the zip folder contains four files (parasetX.csv.gz, X=1, 2, 3, 4) corresponding to the four parameter sets specified in (6). They are the moving trajectories of the car agents with simulated energy and charging time history in their simulation days. <strong>Column</strong> <strong>Description</strong> <strong>Data type</strong> <strong>Unit</strong> person Agent ID Integer - home_charger Whether an agent has access to a home garage charger/living in a detached house (0=no, 1=yes) Integer - car Car model class (B=40 kWh, C=60 kWh, D=100 kWh) String - seq Sequence ID of time history by agent Integer - time Time (0-86399) Integer Second purpose Valid for activities (home, work, school, other) String - type Event type defined by MATSim simulation String - link Link ID (link_id in File 5) String - distance_driven Cumulative driven distance in the simulation day Float km energy_1 Energy consumed while driving (-) or charging (+) (Strategy 1) Float kWh energy_2 Energy consumed while driving (-) or charging (+) (Strategy 2) Float kWh energy_3 Energy consumed while driving (-) or charging (+) (Strategy 3) Float kWh charger_1 Power rating of the charger (Strategy 1) Float kW charger_2 Power rating of the charger (Strategy 2) Float kW charger_3 Power rating of the charger (Strategy 3) Float kW soc_1 State of charge (0-1, Strategy 1) Float - soc_2 State of charge (0-1, Strategy 2) Float - soc_3 State of charge (0-1, Strategy 3) Float -**研究背景** 纯电动汽车（Battery Electric Vehicle, BEV）是构建可持续交通系统的核心支撑。随着纯电动汽车保有量的持续攀升，精准评估充电基础设施的需求变得愈发关键。然而当前多数充电基础设施相关研究仍依赖过时假设：例如默认所有纯电动车主均可使用家用充电桩，以及沿用“燃油车类比”的思维定式。 为解决这一问题，本研究针对三类充电行为原型开展出行与充电需求模拟。研究采用瑞典大规模人工合成人口数据集，涵盖个体详细特征，包括住宅类型（独栋住宅与公寓住宅）以及典型工作日的活动计划。 本数据集仓库旨在公开纯电动汽车模拟的输入参数、假设条件与输出结果，以供其他研究用于充电基础设施规模与布局设计、电网影响评估等相关课题。相关研究方法已发表于《Transportation Research Part D: Transport and Environment》期刊（详见第2.2节「纯电动汽车模拟」），DOI链接：https://doi.org/10.1016/j.trd.2023.103645 **研究方法** 本数据集以瑞典西约塔兰（Västra Götaland, VG）大区的170万常住人口为核心研究对象，该大区包含瑞典第二大城市哥德堡。研究共模拟了28.4万名居住于西约塔兰大区的汽车智能体，这些智能体覆盖了该大区35%的汽车使用者与18%的总人口。模拟时长对应一个典型工作日，智能体的活动轨迹覆盖瑞典全境多个点位。 本开源数据集仓库包含模型核心输入与输出数据，括号内的编号对应各数据集模块。本研究用于纯电动汽车模拟的输入数据包括：智能体活动计划（模块1）、MATSim模拟生成的出行轨迹（模块2）；同时纳入了家用充电桩夜间接入条件（模块3）、匹配瑞典当前私人汽车保有结构的车队构成（模块4）、带坡度信息的瑞典道路网络（模块5），以及贴合实际的纯电动汽车充放电动力学模型。 针对纯电动汽车模拟，本研究共设置了10类充电行为原型与快充功率组合场景（模块6）。模拟输出包含不同场景下纯电动汽车的出行轨迹与充电时序数据（模块7）。 **数据说明** 本数据集共包含7个数据文件。 ### (1) 智能体活动计划 文件名：1_activity_plans.csv | 列名 | 说明 | 数据类型 | 单位 | | ---- | ---- | ---- | ---- | | person | 智能体ID | 整数 | 无 | | act_id | 智能体活动索引 | 整数 | 无 | | deso | 人口统计区域（Demographic statistical areas, DeSO）分区代码 | 字符串 | 无 | | POINT_X | 活动点位X坐标（采用SWEREF99TM坐标系） | 浮点型 | 米 | | POINT_Y | 活动点位Y坐标（采用SWEREF99TM坐标系） | 浮点型 | 米 | | act_purpose | 活动类型（工作、居家、其他） | 字符串 | 无 | | mode | 前往活动点位的交通方式（仅汽车） | 字符串 | 无 | | dep_time | 出发时间（十进制小时，范围0-23.99） | 浮点型 | 小时 | | trav_time | 出行耗时 | 字符串 | 小时:分钟:秒 | | trav_time_min | 出行耗时（十进制分钟） | 浮点型 | 分钟 | | speed | 出行平均速度 | 浮点型 | km/h | | distance | 出行往返距离 | 浮点型 | km | | act_start | 活动开始时间（分钟数，范围0-1439） | 整数 | 分钟 | | act_time | 活动持续时长 | 浮点型 | 分钟 | | act_end | 活动结束时间（十进制小时，范围0-23.99） | 浮点型 | 小时 | | score | MATSim模拟生成的当日效用评分 | 浮点型 | 无 | > 1 https://www.scb.se/vara-tjanster/oppna-data/oppna-geodata/deso--demografiska-statistikomraden/ ### (2) 出行轨迹 文件名：2_input_zip 本文件夹由MATSim模拟生成，为纯电动汽车模拟提供输入事件数据，包含10个压缩文件（events_batch_X.csv.gz，X=1,2,…,10），对应模拟日内汽车智能体的移动轨迹。 | 列名 | 说明 | 数据类型 | 单位 | | ---- | ---- | ---- | ---- | | time | 模拟日时间（秒数，范围0-86399） | 整数 | 秒 | | type | MATSim模拟定义的事件类型² | 字符串 | 无 | | person | 智能体ID | 整数 | 无 | | link | 对应模块5的最近道路路段ID | 字符串 | 无 | | vehicle | 车辆ID，与智能体ID一致 | 整数 | 无 | > ² MATSim模拟事件的典型流程为：活动结束（actend）→ 智能体车辆驶入车流（vehicle enters traffic）→ 车辆从当前路段驶向下一连通路段（left link）→ 智能体车辆驶离车流前往活动点位（vehicle leaves traffic）→ 活动开始（actstart） ### (3) 家用充电桩夜间接入条件 文件名：3_home_charger_access.csv | 列名 | 说明 | 数据类型 | 单位 | | ---- | ---- | ---- | ---- | | person | 智能体ID | 整数 | 无 | | home_charger | 智能体是否拥有家用车库充电桩/居住于独栋住宅（0=否，1=是） | 整数 | 无 | ### (4) 汽车保有结构 文件名：4_car_fleet.csv | 列名 | 说明 | 数据类型 | 单位 | | ---- | ---- | ---- | ---- | | person | 智能体ID | 整数 | 无 | | income_class | 收入等级（0=无数据，1=年收入低于18万克朗，2=18万-30万克朗，3=30万-42万克朗，4=年收入高于42万克朗） | 整数 | 无 | | car | 汽车型号等级（B=40kWh电池容量，C=60kWh电池容量，D=100kWh电池容量） | 字符串 | 无 | ### (5) 带坡度信息的道路网络 文件名：5_road_network_with_slope.shp（共5个文件） | 列名 | 说明 | 数据类型 | 单位 | | ---- | ---- | ---- | ---- | | length | 道路路段长度 | 浮点型 | 米 | | freespeed | 自由流速度 | 浮点型 | km/h | | capacity | 路段通行容量 | 整数 | 无 | | permlanes | 车道数量 | 整数 | 无 | | oneway | 路段是否为单向通行（0=否，1=是） | 整数 | 无 | | modes | 允许的交通方式（仅汽车） | 字符串 | 无 | | link_id | 路段ID | 字符串 | 无 | | from_node | 路段起始节点ID | 字符串 | 无 | | to_node | 路段终止节点ID | 字符串 | 无 | | count | 日累计交通流量（每日通行车辆数） | 整数 | 无 | | slope | 道路坡度（百分比，范围-6%至6%） | 浮点型 | 无 | | geometry | 几何形状（采用SWEREF99TM坐标系的线要素） | 几何类型 | 米 | ### (6) 模拟场景参数集 文件名：6_scenarios.txt | 参数集编号（paraset） | 策略1占比 | 策略2占比 | 策略3占比 | 快充功率（kW） | 最低充电停留时长（min） | 慢充功率（kW） | | ---- | ---- | ---- | ---- | ---- | ---- | ---- | | 0 | 0.2 | 0.2 | 0.9 | 150 | 5 | 22 | | 1 | 0.2 | 0.2 | 0.9 | 50 | 5 | 22 | | 2 | 0.3 | 0.3 | 0.9 | 150 | 5 | 22 | | 3 | 0.3 | 0.3 | 0.9 | 50 | 5 | 22 | ### (7) 纯电动汽车模拟的出行与充电时序数据 文件名：7_output.zip 本文件夹由纯电动汽车模拟生成，包含4个压缩文件（parasetX.csv.gz，X=1,2,3,4），分别对应模块6中定义的4组参数集，包含模拟日内汽车智能体的移动轨迹、模拟能耗与充电时序数据。 | 列名 | 说明 | 数据类型 | 单位 | | ---- | ---- | ---- | ---- | | person | 智能体ID | 整数 | 无 | | home_charger | 智能体是否拥有家用车库充电桩/居住于独栋住宅（0=否，1=是） | 整数 | 无 | | car | 汽车型号等级（B=40kWh电池容量，C=60kWh电池容量，D=100kWh电池容量） | 字符串 | 无 | | seq | 智能体时序数据序列ID | 整数 | 无 | | time | 模拟日时间（秒数，范围0-86399） | 整数 | 秒 | | purpose | 活动类型（仅适用于活动时段，包含居家、工作、上学、其他） | 字符串 | 无 | | type | MATSim模拟定义的事件类型 | 字符串 | 无 | | link | 路段ID（对应模块5的link_id字段） | 字符串 | 无 | | distance_driven | 模拟日内累计行驶里程 | 浮点型 | km | | energy_1 | 策略1下的能耗（行驶为负值，充电为正值） | 浮点型 | kWh | | energy_2 | 策略2下的能耗（行驶为负值，充电为正值） | 浮点型 | kWh | | energy_3 | 策略3下的能耗（行驶为负值，充电为正值） | 浮点型 | kWh | | charger_1 | 策略1下的充电桩功率 | 浮点型 | kW | | charger_2 | 策略2下的充电桩功率 | 浮点型 | kW | | charger_3 | 策略3下的充电桩功率 | 浮点型 | kW | | soc_1 | 策略1下的电池荷电状态（范围0-1） | 浮点型 | 无 | | soc_2 | 策略2下的电池荷电状态（范围0-1） | 浮点型 | 无 | | soc_3 | 策略3下的电池荷电状态（范围0-1） | 浮点型 | 无 |