How to benefit from innovative electric fleet charging solutions — a case study

Updated: Nov 5


Combine fleet management and electric vehicle charging

Do you know the number one challenge for electric fleet managers?


(Hint: It’s not battery range!)


Most people think that the battery range is the biggest issue. In actual fact, the biggest problem is how to manage a large number of electric vehicles (EVs) at one location.

It makes sense when you think about it.


The charging demands of a large electric fleet put a lot of strain on the electricity supply and require good infrastructure and innovative charging solutions.


Why you should research EV fleet charging solutions


McKinsey estimates that fleet EVs can have a total cost of ownership that is 15 to 25 percent less than equivalent Internal Combustion Engine ICE vehicles by 2030.


For this reason, combined with increasing legislation and government targets, many companies are looking to build electric fleets over the next decade.


But, the only way fleet managers can make these considerable cost savings is if they manage their day-to-day business in line with fleet operations.

Day-to-day business activities include:

  • Delivering packages

  • Transporting people from A to B

  • Providing vehicles to employees

  • Providing vehicles to the public for hire

EV fleet operations include:

  • Ensuring batteries are fully charged.

  • Avoiding or minimizing delays and vehicle downtime.

  • Coordinating vehicles and charge points.

But how can you align both the objectives of your electric fleet and your day-to-day business activities?


This article will outline a relevant use case and provide an in-depth analysis of how both fleet and business objectives can be achieved.


Case Study: A classic taxi fleet, or vehicle for hire service


The use case we’re presenting in this article is a business that offers transportation to people, whether a taxi for hire or rental vehicles.


As a guide, think of services such as Uber, Lyft, Via, Grab, or a traditional taxi fleet.


For the purpose of this study, we’re going to assume that the company is planning to have a 100% electrified fleet by 2025 and are preparing for this now. They are entirely committed to reducing GHG emissions with electric vehicles but can only allocate a limited budget to invest in charging stations, electric vehicles, and new software systems.


They plan to charge 100 vehicles at several locations, with the vehicles charging at night and operating during the day. To begin moving towards this goal, they want to install new charge points over the next six months.


In this case, the project manager or fleet manager has three main goals:

  1. Install and manage the transition to the EV fleet according to the timeline

  2. Manage the budget for setups, EV cars, and software systems

  3. Ensure smooth operation of the new electric car fleet (e.g., departure times)

We’ll now examine two possible scenarios. The first is non-optimized charging, and the second involves a focus on optimized charging. We’ll discuss the outcomes of each approach and weigh up the pros and cons.


Scenario 1: Non-optimized charging: big project costs and high total cost of ownership


In this scenario, you’ve performed an analysis and identified how your new electric taxi fleet will operate at that location.


The following parameters apply:

  • 100 electric vehicles each 75 kWh on average

  • Vehicles have a stay-time at the depot: 10 hours on average

  • You plan to get 100 charging stations with 11.5 kW each (level 2)

  • Arrival time is between 9 PM and Midnight

  • Departure time is between 4 AM and 9 AM the next day


Assumptions for the case study: EV fleet charging

At this point, you believe that you’re all set to go ahead with the plan and begin the installation.


Then it happens.


The utility service provider explains that you can’t get enough power capacity for this number of vehicles. They need to plan and execute grid constructions to install new transformers and gridlines for your EV charging stations. That will cost several million dollars and take at least 12 months to plan, get approvals, and execute the construction.

Why?


The EV charging stations will require a total capacity of 1,200 kW. Unfortunately, the selected site has only a portion of that capacity available.


This is what one day of operation will look like:


All vehicles begin charging immediately when the driver plugs the vehicle into the charge point. This leads to a peak of 1,200 kW. Any additional charging station that you install later on would increase the peak power demand even more.

Cumulated load curves for uncontrolled EV fleet charging, Y-axis (power in kW), X-axis (date-time 8 AM to 12 AM)

In this case, your overall project would fail for two reasons:


a) you have to delay the entire project by at least six months. As a result, the company will not be able to achieve their strategic KPI of being 100% electric by 2025.


b) you will exceed the planned budget for the electrification. This is only one location, and your calculation shows that the other site will face similar challenges. That would lead to nearly a billion-dollar additional unplanned investment over the coming years.


However, you also find another interesting result: Your analysis shows that all your vehicles seem to be fully charged between 3 AM and 5 AM. And the majority actually before 4 AM.

Charging events for uncontrolled EV fleet charging, X-axis (date-time 8 AM to 12 AM the next day)

You decide to perform a second analysis. This time you assume that your company uses a new optimization technology for intelligent EV fleet charging.


Scenario 2: Optimized charging: lean management and smart charging


In this scenario, your optimization software for your electric fleet will connect to the vehicles, the charging stations, and other relevant fleet management systems.


It takes into account several parameters of your electric fleet cars, such as the remaining energy in the batteries and the departure time of each vehicle.


So, you set the system for analysis, and the results are surprising:

  • The simulation shows that you need 30–40% less power capacity for your EV charging location than before.

  • At the same time, all the EVs are fully charged at their individual expected departure time.


Cumulated load curves for optimized, Y-axis (power in kW), X-axis (date-time 8 AM to 12 AM the next day)

Charging events for uncontrolled EV fleet charging, X-axis (date-time 8 AM to 12 AM the next day)

Charging events for uncontrolled EV fleet charging for 100 electric vehicles: X-axis (date-time 8 AM to 12 AM the next day) provided by Ampcontrol


With this new analysis in hand, you schedule a second appointment with your utility provider.

And great news! They approve the plan. No grid construction and additional power capacity are required.


What this means in practical terms is that you stay below budget, maintain the project timeline, and you have identified a new technology to help your fleet operators in managing the charging of the electric vehicles.


Getting ready to connect your fleet management system and smart charging


It’s a no-brainer. You decide to go with the second scenario of optimized charging.

The next step is to work out how to connect your fleet management system with the smart charging solution.


Each new electric van, truck, or car increases the complexity of charging the car and scheduling your fleet.


It’s a risky strategy to let your fleet manager or driver schedule charging processes manually. Using local load management systems is a possible approach, but they are usually limited to a small number of charging stations and do not communicate with your fleet system or vehicles.


Therefore, it’s recommended to use newer technology. The latest trend is to use fully cloud-based solutions for the optimization of electric vehicle fleets.


Cloud solutions are often more stable and secure as they have various backup functions built-in with remote servers. Additionally, optimization methods on cloud services are more scalable and robust than local ones.


By connecting vehicles, fleet management systems, and intelligent charging software, the entire optimization happens in the background. All the drivers need to do is plug in the vehicles.


This cloud-managed approach can be used for buses, vans, passenger cars, or any type of vehicle.


The main advantage of this is that most of the time, the information is already available in the current fleet management system. If not, you can also add small affordable IoT devices to track GPS and battery data in real-time, for example.


The beauty of it is that the software applies algorithms and machine learning tools automatically to take over math and analysis. The software will control the charging schedules with the sole focus of reducing costs and sticking to the scheduled program.


Conclusion


Here are the key takeaways from the use case described above:

  • The electrification of fleet vehicles usually has tight time or budget constraints.

  • If you don’t apply any optimization software, such as Ampcontrol, you’ll get project delays and unplanned expenses.

  • The right software ensures low power demand at EV charging locations while also guaranteeing the on-time departure of vehicles.

  • Connecting the fleet management system for vehicles and EV smart charging software systems is key to automate the process successfully.

  • Cloud-based solutions such as Ampcontrol offer the most cost-effective and convenient way to achieve this.

At Ampcontrol, we’ve developed the technology to optimize fleet charging through the cloud. We are successfully helping charging networks and fleet operators around the world to electrify their fleet vehicles.


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