Route optimization with charging infrastructure

Genesis NGN created a route optimization solution for a transportation company trying to switch to EVs so that available charging infrastructure can be leveraged with as much running time as possible.

Route optimization 

Route optimization, also known as the Traveling Salesman problem, is one of the most talked about and solved algorithms by mathematicians globally. With the advent of EVs, the charging infrastructure has become another variable in this problem. If existing route optimization algorithms are followed, the vehicles would be stranded on the roads due to a lack of charging. So, charging infrastructure adds another complexity to route optimization that needs to be efficiently managed.

Our Client 

Our client is a global transportation company operating in many countries. They provide various transportation services to small as well as large businesses.

The Challenge

Due to huge fuel costs, they have been switching to EVs wherever possible. And the aim is to have 50% of their vehicles to be EVs by 2030. However, due to the lack of sufficient EV infrastructure, route optimization has become a big problem for them. The traditional route optimization algorithm does not factor in the availability of the charging infrastructure or the distance that a vehicle can travel on one charge, and as a result, those cannot be used. This forced their team to manually create routes for EV vehicles, which is a huge time drain as well as inefficient. This has created a situation where a lot of vehicles are standing at one place for charging and very few vehicles are actually transporting the goods.

The Solution

We leveraged our expertise in the logistics industry to fully understand the problem and then collaborated with mathematicians of some of the best universities to find a solution. The result was a route optimization algorithm software specially designed for EVs that ensured all of the following:

  1. Understood that different types of vehicles have different mileage per charge and need different charging time.
  2. Understood that some charging infrastructure might not be suitable for all vehicles.
  3. Understood that the queue at the charging infrastructure also needs to be managed so that it should not happen that one charging station is empty while others are over-occupied.

Keeping all the above constraints in mind, the route optimization software achieved the following:

  1. Create an exact route for each vehicle based on charging capacity
  2. Included nearest charging station as a part of the overall route
  3. Made sure all charging stations are optimally utilized
  4. Had guidance around “emergency” charging infrastructure
  5. Connected with charging sensors of vehicles to gauge real-time charging left.
  6. Alerted staff at the charging stations about upcoming vehicles.

Results

As a result of the new route optimization software, the client achieved the following successes:

  1. EVs were on roads for longer
  2. Existing charging infrastructure was more optimally managed
  3. More EVs could be added confidently
  4. Reduced lead time to achieve profitability for EVs
  5. More insight into the efficiency of each EV as well as a better understanding of the seasonal impact on efficiency.