Electrification of Bus Transport

There are plenty of factors which require careful planning when it comes to management of bus transport, including route planning; driver scheduling and shifts; and vehicle maintenance. Fuel, however, is not typically one of them.

Today, most vehicles are able to carry a full day’s worth of fuel, simply refuelling at depots overnight. The risk of running dry mid-journey; and the matter of when, where and how to schedule refuelling stops throughout the day, are not factors with which operators have needed concern themselves.

However, the era of electric vehicles will, of course, radically change this situation.

On the one hand, electrification requires bus schedulers to consider a question they have never before had to work with: how do you manage scheduling and route planning when buses require recharging through the day? On the other, electrification also has the potential to introduce a whole new scale of efficiencies, both in terms of day-to-day bus operations, and longer-term planning and scheduling.

In short, electric vehicles could utterly reshape the transport networks of the future and how they are managed.

The downside

The major downside of electrification in the bus industry is that a single battery charge will, at least for the next few years, not be sufficient to drive a bus for a whole day. In other words, intermediate charging will be necessary throughout the day, and this will
need to be taken into account when scheduling the bus. A new factor is therefore layered into the process of bus scheduling, and this means scheduling algorithms need to become more sophisticated.

In the electric era, bus scheduling algorithms will need to look at the increased need to calculate a bus’s optimal route and charging times, to ensure the vehicle asset can be utilised as fully as possible. Real-time prediction of what the bus is going to do becomes absolutely essential in this scenario, because buses cannot be allowed to run out of electricity before reaching a charging point.

This requires Internet of Things (IoT)-enabled sensors which are able to measure not only the location of the vehicle, but also the battery’s remaining charge; as well as factors which will affect how quickly it drains – including the likely speed of travel, number of passengers and any other loads, energy usage from in-vehicle USB charging, and weather conditions. And of course, there is also a requirement for an algorithm which can analyse all of this information on an ongoing basis – along with the time it will take the bus to recharge at the next stop – and feed all these calculations into broader bus scheduling.

This means that machine learning and predictive analytics will become essential tools in order to avoid potential headaches for operators.