Operating electric buses for public transport poses some special challenges in relation to the charging infrastructure, route planning and operational management. The MENDEL research project provides the basic principles for an ideal charging infrastructure and defines the scheduling and operational requirements for the transport company.
Electromobility in public transport
Optimised charging processes
About the MENDEL research project
At the beginning of 2016, INIT started to work on the MENDEL research project, together with its partners: AVT STOYE GmbH, Institut für Verkehrssystemtechnik am Deutschen Zentrum für Luft- und Raumfahrt e.V. [the Institute of Transportation Systems at the German Aerospace Centre], Fraunhofer Institut für Materialfluss und Logistik [Fraunhofer Institute for Material Flow and Logistics], GEVAS software Systementwicklung und Verkehrsinformatik GmbH [GEVAS software System development and Traffic automation], Institut für Automation und Kommunikation [Institute for Automation and Communication] and the associated partners of BS|NETZ Braunschweiger Netz GmbH and Braunschweiger Verkehrs-GmbH.
The project funded by the Federal Ministry for Economic Affairs and Energy is intended to align the interests of energy providers with those of transportation companies.
The aim is to establish the foundations of a cost-efficient charging infrastructure which caters for the specific requirements of electric buses in public transport. The primary goals of the MENDEL project are therefore:
Goal 1: Minimising investment costs
Avoiding installing additional substations to supply energy to the charging sites through optimal use of the existing low-voltage distribution grids. In general, the number of charging stations should be kept as low as possible. In this way, the infrastructure that already exists can be used as efficiently as possible.
Goal 2: Minimising operating costs
The charging processes should be planned so as to minimise the peak energy consumption that determines the contract price, by balancing the charging processes across both locations and time. This also reduces the fixed operating costs for the charging infrastructure, that are reflected in the base price of supply. The variable operating costs of the e-fleet shall be further reduced by minimising energy consumption by the buses and improving route planning. Various sub-goals were set in order to achieve both of these primary goals. These include strategic aspects, such as improved scheduling of vehicle usage combined with improved infrastructure planning, tactical aspects such as improved load management during operations, and operational aspects, such as improved driving style during operations (low-consumption driving):
Sub-goal 1: Improved vehicle scheduling (strategic level)
When scheduling routes and services, the required charging processes must be taken into consideration as an additional variable. The aim is to use optimisation algorithms to resolve the conflicting aims of efficient running and a minimum peak load on the electricity network. The peak load is calculated as the sum of the power requirements of the maximum number of buses to be charged at the same time. The power requirement of each individual bus is derived from the initial battery charge plus the energy consumed until the next charging station is reached and the charge time available.
In addition to the planned charge times, time buffers need to be taken into account in the blocks, to compensate small delays due to any interim charges required. These may, for example, be needed if the charging process at a planned stop did not result in the required charging level. It is also necessary to factor in so-called energy buffers, i.e. it must be possible to cover any fluctuations in the currently available charging capacity across the entire charging network, so that even if a bus is not charged to maximum capacity it is still certain to reach the next charging station. It should be noted that the more buffer times need to be built in, the more buses the transport company needs to use to cover the schedule.
Sub-goal 2: Optimal infrastructure planning (strategic level)
The more charging stations are installed, the better the spread of the charging demand. As a result the peak charge load will fall across the entire electricity network as well as the operating costs of public transport. But at the same time, the number of charging stations needs to be kept to as few as possible to minimise the investment and operating costs for the energy network operator. The number of charging stations also diametrically affects the number of buses required to meet the timetables, because the lower the number of charging stations, the more buffers need to be planned in, as described in sub-goal 1.
The aim of infrastructure planning is to determine the optimal locations of the charging stations to achieve overall efficiency. It is important to resolve these conflicting goals applying both optimisation algorithms and strategic considerations.
Sub-goal 3: Optimal charge management during operations (tactical level)
To be able to react to operational fluctuations from the planned charges which are not covered by the planned buffer times, or fluctuations in performance, appropriate information and communication technologies (ICT) need to be installed. Specifically, smart services should be developed that optimise the charging processes with regard to load management. They will take account of the current charging status of the buses, their estimated energy requirements and the currently available maximum performance at the sites, as well as the primary goal of the minimum overall charging capacity. If necessary, these services subsequently impose operational driving instructions, such as extending the time spent at charging sites.
Sub-goal 4: Optimal route strategy for operations (operational level)
Minimum energy requirements of the buses are also beneficial to achieve the aspired overriding goals. Major savings can be achieved by avoiding frequent stops, as the accelerating process is inevitably energy-intensive. The most common reason for this avoidable energy consumption are traffic lights in urban traffic. This should be avoided by using transport management systems which receive real-time information from the ITCS on the current operating status and react accordingly.