Driving Range Estimation and Trajectory Planning

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Driving Range Estimation and Trajectory Planning ( driving-range-estimation-and-trajectory-planning )

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Implementation into the Delivered Application The Interface of Developed HMI Figure 7.2: Settings for the Developed Application. From the top in Fig. 7.2, we can see the value for the SoC. This value is here for test purposes and will be inactive when connected to the Demo vehicle because this value will be obtained from the CAN signal of the vehicle. The next value defines the battery capacity. This value can be changed according to the vehicle we are connected with. The average consumption value will be also inactive when connected to the vehicle and we also get it from the CAN signal of the vehicle. The next parameter is Goal capacity. This parameter means how much energy should be once the destination will be arrived, which the algorithm takes it into account. I consider as possible that the vehicle can always charge the battery at the destination, but with a low-current charger (22kW or less). The next parameter is a switch named, ”Traffic With Duration”. This parameter allows us to return actual traffic conditions through a planned route, and we can obtain a more accurate result using it, because the database of charging stations was updated at different times and without traffic information included. Unfortunately, we don’t obtain exact in- formation about possible delays but only time information about how long the trip would take. Google does not provide such detailed information nowadays. Finally, there can be chosen to configure how fast and accurate we want to obtain the results using the developed algorithm. There are three options (fast, medium, or very accurate), as described already in chapter chapter 6 of this thesis. 37

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