ISEA RWTH Aachen Electric Bus Simulation

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1 ISEA RWTH Aachen Electric Bus Simulation Finding the Optimal Technical Configuration Fabian Meishner Lehrstuhl für Elektrochemische Energiewandlung und 1 Speichersystemtechnik

2 Electric Bus Simulation - Motivation Theoretical evaluation of technical feasibility Charging times & power, Battery energy capacity Evaluation of different technological concepts before implementation / demonstration Overnight/Opportunity-Charging, different Battery technologies Fast & valuable results, if input data is as realistic as possible Check robustness against Worst-Case conditions Estimation of resulting (technical) Project costs Optimization of technical configuration in order to decrease costs 2

3 Example 3 new Electric Buses on Line 73 in Aachen Stop 4 Stop1 Line 73 Stop2 Bus depot Stop 5 Stop9 Stop3 Stop 6 Stop8 Stop 7 Final stop 3

4 Driving Profiles from vehicle schedules Detailed route is taken as a basis including: Traffic lights speed zones height profile curves 4

5 From Route to Load Profiles Route Profile Vehicle- and Driver model Tract. resistance Reg. Braking Efficiency Powertrain Engine Power Electronics Battery Aux. Consumers Heating/AC P el With help of a vehicle model, the power requirement at each time point is calculated from the route profile 5

6 Finding the configuration with lowest TCO Optimization variable Battery capacity? kwh Charging station Stop1? kw Charging station Stop3? kw Charging station Stop4? kw Charging station Stop6? kw Charging station Stop8? kw Bus Depot? kw Other parameter Investigation timeframe 12 years Interest rate 4 % 6

7 System Model Power-Supply Charging station Aux. consumers Vehicle Building cost subsidy, Connection charge, * Network charge Constructional measures DC DC AC DC DC El. Machine AC Grid connection Trans- DC former + Rectifier DC Charging control Coupling assembly DC-Link Communication Battery 7

8 TCO composition Energy: Diesel (per litre; incl. taxes and excise taxes) Electricity (per kwh; incl. subsidies and taxes) Grid utilization fees (per kw and per kwh) Charging infrastructure: Charger (asset + maintenance) Coupling device (asset; stationary part) Grid connection costs (one-time expenses) Constructional measures (one-time expenses) Battery system Cells, packaging, system components (asset) Maintenance (for vehicles) Maintenance costs (per km) Insurance costs (annual costs) Vehicles Vehicle (asset; incl. e-machine / diesel engine) Coupling device (asset; on-board part) No battery system (see above) 8

9 Optimization Loop Data Base Schedules Parameters Optimization Battery Capacity Location and Power of Charging Stations Scenario Algorithm adjusts configuration Fitness function Simulation TCO Penalties Optimized configuration with lowest TCO 9

10 TCO Calculation (1) Stop1 Example Stop3 Optimization Stop4 Loop Stop8 Stop6 Depot Resulting TCO:

11 Optimization Loop Stop1 Stop3 Stop4 Stop8 Stop6 Depot Optimization terminates after 1600 iterations 11

12 Result Stop1 Stop3 Stop4 Stop8 Stop6 Depot 12

13 Exemplary: Daily load of vehicle 3 13

14 Final Result Optimization variable Battery capacity 125 kwh Charging station Stop1 125 kw Charging station Stop3 0 kw Charging station Stop4 0 kw Charging station Stop6 0 kw Charging station Stop8 270 kw Bus Depot 100 kw Cash value of resulting total costs: 2,38 Mio. 14

15 ISEA RWTH Aachen Electric Bus Simulation Finding the Optimal Technical Configuration Fabian Meishner Lehrstuhl für Elektrochemische Energiewandlung und 15 Speichersystemtechnik

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