EV-Routing-Algorithm

This repository contains a simple routing algorithm for electric vehicles. This algorithm takes a model of an electric vehicle that is described by some parameters and computes the consumption of it for the driven route. If the route cannot be driven without a charging stop, the algorithm selects charging stops along the route.

Setup

RoutingKit

The RoutingKit requires zlib to work:

sudo apt-get install zlib1g-dev

Download your map as a .pbf file from Geofabrik and copy it into the data folder. Make sure to paste the name of the file as pbf_file into the loadGraph() method in src/Main.cpp. If you run the program for the first time for this graph, you need to make sure that the boolean precomputed is set to false. This will run the contraction hierarchy computations and save the result in a separate file. Afterwards you can set precomputed to true and save some time.

You can also use boost to check for the existence of the file automatically. In this case you need to uncomment the line in loadGraph() in include/Graph.h

Charging stations

This routing algorithm also requires a list of charging stations provided as charger.csv in the data directory. Such list can be created with the gatherEVStations.py script which uses the TomTom API to collect such a list. However, you need your own API Key that you paste in the INSERT_API_KEY_HERE field at the beginning of that script. You can apply for a Key on the TomTom Webpage after you registered.

You also have to adapt the bounds array and countryCode in the main function. The bounds are the top-left and bottom-right coordinates of the country and are used for the search process.

After you adapted these values you can run the script with

python3 gatherEVStations.py

Using this code

Building

Make sure you have CMake installed:

sudo apt install cmake

In the file called platform.txt you need to enter your platform in a single line (default: WSL, other options: NATIVE_UNIX, WINDOWS).

If you use the CMake extension from VS Code you can choose the "Build All Projects" options in the CMake tab to build the project.

You can then execute

cd build
./Routing

to run the code. This should print some information of the loading process to the console create an output.json file in the build directory. This is the calculated route of the algorithm.

Parameters

You can change the start and destination of the route in calculateExampleRoute() in src/Main.cpp. There you can also define the electric vehicle that you want to use.

In main() you need the insert the name of the graph that you want to use and set the precomputed value accordingly.

Note: You need to recompile the project after changing those values before running it.

Result

The result of the routing algorithm will be exported as JSON. This response is structured just like the result from the TomTom Long Distance EV Routing API. However, since this may change you should check the exampleResult.json file to get an overview of the provided information.

Visualization

You can use the basic webpage from this repository to upload the output.json file and get an interactive visualization of the JSON result.

Electric Vehicles

Here are some code snippets for four vehicles that can be used in the Main.cpp file.

Tesla Model 3 LR

EvCar car = EvCar("Tesla Model 3 LR", 70.0, "10,10.7:50,10.7:80,13.3:120,16.3");
car.weight = 2019;
car.setChargingCurve({{ 7.0, 190 }, { 7.7, 187 }, {8.4, 182}, {9.1, 175}, {9.8, 170}, {10.5, 166}, {11.2, 162}, {11.9, 159}, {12.6, 156}, {14.0, 150}, {14.7, 148}, {15.4, 147}, {16.1, 145}, {16.8, 144}, {18.9, 138}, {19.6, 136}, {21.7, 131}, {22.4, 128}, {23.1, 126}, {23.8, 124}, {24.5, 122}, {25.2, 120}, {25.9, 118}, {26.6, 116}, {28.7, 109}, {30.8, 102}, {31.5, 99}, {32.2, 97}, {32.9, 95}, {33.6, 92}, {34.3, 90}, {35.0, 88}, {35.7, 86}, {36.4, 85}, {37.1, 83}, {37.8, 81}, {38.5, 79}, {39.2, 77}, {39.9, 75}, {40.6, 72}, {41.3, 70}, {42.0, 69}, {42.7, 67}, {43.4, 66}, {44.1, 64}, {44.8, 64}, {46.9, 60}, {50.4, 56}, {51.1, 54}, {53.9, 50}, {56.7, 45}, {59.5, 40}});

Volkswagen ID.4

EvCar car = EvCar("Volkswagen ID.4", 77.0, "10,12.8:50,12.8:80,16.4:120,20.5");
car.weight = 2224;
car.setChargingCurve({{0.0, 122}, {3.85, 127}, {7.7, 126}, {11.55, 127}, {15.4, 127}, {19.25, 126}, {23.1, 124}, {26.95, 117}, {30.8, 108}, {34.65, 99}, {38.5, 92}, {42.35, 85}, {46.2, 75}, {50.05, 68}, {53.9, 65}, {57.75, 64}, {61.6, 60}, {65.45, 43}, {69.3, 35}, {73.15, 26}});

Renault Zoe

EvCar car = EvCar("Renault Zoe", 52.0, "10,10.9:50,10.9:80,14.2:120,18.2");
car.weight = 1677;
car.setChargingCurve({{1.56, 44}, {2.6, 44}, {5.2, 45}, {10.4, 45}, {13.0, 46}, {15.6, 44}, {18.2, 42}, {20.8, 40}, {23.4, 39}, {26.0, 36}, {28.6, 33}, {31.2, 31}, {33.8, 29}, {36.4, 26}, {39.0, 25}, {41.6, 24}});

Fiat 500e

EvCar car = EvCar("Fiat 500e", 37.3, "10,10.5:50,10.5:80,13.8:120,17.3");
car.weight = 1465;
car.setChargingCurve({{2.98, 72}, {3.73, 76}, {5.6, 82}, {7.46, 85}, {9.32, 82}, {11.19, 80}, {13.06, 74}, {14.92, 68}, {16.78, 67}, {18.65, 66}, {20.52, 58}, {22.38, 53}, {24.24, 53}, {26.11, 51}, {27.98, 47}, {29.84, 44}, {31.7, 15}});

Dependencies

This repository uses json for creating an output that can easily be visualized.

It also uses RoutingKit for the graph and basic routing.