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Driving Range Polygon Designing Algorithm for Driving Range accurate than considering 100 percent. With the help of the Google API the circle could be displayed as follows: GoogleMap map; Circle circle = map.addCircle(new CircleOptions() . center (new LatLng( latitudeValue , longitudeValue )) . radius (10000) // in meters . s t r o k e C o l o r ( C o l o r . RED ) . strokeWidth (4) .fillColor(Color.argb(140, 192, 192, 192))); The following code is to create a polygon on the map. It consists of several location points connected by a closed curve to create a polygon shape. GoogleMap map; Polygon polygon = map.addPolygon(new PolygonOptions() .add(new LatLng(0, 0), new LatLng(0, 5), new LatLng(0, 0)) . strokeColor ( Color .BLUE) . f i l l C o l o r ( C o l o r . BLUE ) ) ; In the algorithm is considered the driving range from the Demo vehicle. This driving range is counted as a SoC divided by an average consumption for last 20 minutes of driving. Following is the equation how the driving range is counted in the vehicle. d = SoC(kW h) · 100 avg. consumption for last 20 min(kWh) During the real test on Demo vehicle wasn’t, unfortunately, the algorithm correctly cali- brated. Due to this fact, I was forced to set the average consumption for last 20 minutes as a constant parameter (20 kWh/100km). For any other additional information, I don’t use in the algorithm because the Demo vehicle does not provide any. When designing an algorithm the idea is based on current location which could be obtained from a provider. The Google API does not return distance as the polygon. At the begin- ning, I used Google Distances Matrix API because the purpose is to get the only value of the distance between points. I use Haversine formula to count great-circle distance in the algorithm. 15PDF Image | Driving Range Estimation and Trajectory Planning
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