After the idea for VoltSim was born on a film set, it didn’t take long before I realized: I don’t just want to think about this. I want to see it. That’s exactly how the EV Charging Simulator came to be. Of course, I could roughly imagine that an electric shuttle could recharge quite a bit during a downtime of twenty, thirty, or sixty minutes. But that “roughly” was exactly the problem for me. When it comes to electric cars, a lot of the discussion is based on gut feelings. Some say charging always takes too long. Others say modern electric cars charge fast enough. But if you don’t calculate with specific vehicles, specific charging capacities, and specific time windows, both sides end up being nothing more than claims.
The initial idea behind VoltSim wasn’t particularly complicated, then. I wanted to know what happens when a specific vehicle with a specific battery level pulls up to a specific charging station. How long does the charging process take? How much energy goes into the battery? What is the approximate range resulting from that? And above all: What happens if the vehicle doesn’t charge for half an hour or an hour, but only for a few minutes? It was precisely this question that interested me so much because of the shuttle situation on the film set. There, it’s not always about charging a vehicle perfectly from ten to eighty percent. Sometimes a shuttle just sits around for a short while—maybe five minutes, maybe twelve minutes, maybe twenty minutes. And then the real question arises: Does this time matter at all, or can it be put to good use?
In the large screenshot of the main view, you can see quite clearly how I implemented this idea. On the left is the configuration; on the right, the simulation generated from it. You can select a vehicle, set the charging type—AC or DC—specify the charging power of the station, set the starting charge level, and determine the target charge level. Added to this are factors such as battery temperature, preconditioning, and later, more precise temperature values. The example deliberately shows a large van scenario because that fits the original film set question. We’re talking about vehicles that can be thought of as shuttles, Vitos, V-Classes, or similar van classes. In other words, exactly the kind of vehicle you often see on productions and that is sometimes surprisingly underutilized on short trips.
What was important to me here: The charging station alone does not decide. The screenshot shows a very high charging power for the station. Nevertheless, VoltSim indicates that the vehicle itself is the limiting factor. This is a point that gets lost in many discussions. Just because there is a 300-kW or 500-kW station somewhere does not mean that every vehicle can actually handle that power. The car has its own maximum charging power. The battery has a state of charge. The battery level plays a role. Temperature plays a role. And at some point, the charging power drops off, even though the battery continues to charge. That’s exactly why I didn’t want to just display a simple final number, but rather show a charging curve.
For me, this charging curve is one of the most important parts of VoltSim. The green line shows the charging power, the blue line the battery level. This allows you to see not only that charging is taking place, but how it is taking place. In a good charging range, the power remains higher; later, it drops off. This explains much better why a short charge sometimes yields more than you might think, and why the last few percent often take significantly longer. This is particularly relevant in shuttle scenarios. In those situations, no one necessarily needs to ask how long it takes a vehicle to charge from zero to one hundred percent. Much more interesting is the question of what happens between a realistic starting charge level and a reasonable target range.
That’s why I built in the time limit feature. In the screenshot showing the time limit, for example, you can see that you can enter five minutes. VoltSim then shows what SoC is reached after those five minutes, how many kilowatt-hours have been recharged, and what the approximate charging power is at that moment. This was conceived directly from observations on the film set. If a shuttle isn’t needed and can stop briefly at a fast charger, I don’t want to simulate an entire charging session first. I want to know what this specific time window yields. Five minutes isn’t much. But if a vehicle is in the right charging range, even five minutes can suddenly mean a significant amount of energy.
That’s exactly where VoltSim becomes more than just a standard charging time calculator for me. Many tools answer the question: How long does it take to get from A to B? I also wanted to ask: What happens after X minutes? That’s much closer to the real-world processes I observed on set. A driver might not be told, “You now have exactly 37 minutes of charging time.” Instead, a vehicle tends to sit idle until it’s needed again. When you can then see what five, ten, twelve, or twenty minutes yield, the discussion becomes much more concrete.
At the bottom of the main view, you can also see the cost comparison with a similar combustion engine vehicle. In my example, a diesel van is used as a comparison because it fits the shuttle concept. You can distinguish between gasoline and diesel, adjust fuel consumption figures, and change fuel prices or electricity rates. My goal wasn’t to build a perfect accounting system. There are too many variables for that: purchase price, insurance, maintenance, residual value, electricity rates, public charging prices, fuel prices, driving profile, and actual usage. But as a rough comparison, it’s interesting. If an electric vehicle incurs lower energy costs for the same range, you see that immediately. If the difference is smaller, you see that just as clearly. The simulator isn’t meant to sugarcoat the numbers, but to make them visible.
The “Costs & Amortization” section goes one step further. The screenshot shows a simple model calculation over five years, including total EV costs, total combustion engine costs, energy costs per hundred kilometers, and an estimated break-even point. This is intentionally kept simple. I didn’t want to build complicated financial software, but rather an easy-to-understand calculator that points in a direction. When someone compares an electric car with a comparable combustion engine vehicle, they should be able to see roughly when the higher or lower purchase costs might be offset by operating costs. Here, too, the calculation is only as good as the assumptions you enter. But that’s exactly the point. You can change the assumptions and see how much the result shifts.
At the same time, the vehicle database has continued to grow. As of April 25, 2026, there are 603 vehicle entries in VoltSim. These aren’t simply 603 completely different cars, but rather models including variants, battery sizes, and special editions. I’ve tried to cover as many relevant vehicles as possible, not just the obvious German or European electric cars. The database also includes plug-in hybrids, microcars like the Fiat Topolino, and some international or Asian models. However, comparing these vehicles is more difficult because not all values are measured according to the same standards.
That is precisely why VoltSim displays a note in the comparison view when different range standards are used. In the screenshot showing the vehicle comparison, for example, you can see that a European model and another model based on WLTC/CLTC are listed side by side. The range figures are then only comparable to a limited extent. This is important to me because range figures can quickly give a false sense of security. WLTP, WLTC, CLTC, or other measurement methods are not simply interchangeable. When comparing an ID.6, an ID.7, an ID.ERA, or other models from different markets side by side, you need to know that the range figures aren’t always based on the same criteria. That’s why, in such comparisons, metrics like charging time, energy charged in kWh, and charging power are often more meaningful than just the mileage figure.
The Pro comparison feature is currently in development and partially available. The screenshot shows that multiple vehicles can be displayed side by side in a table. The plan is to compare up to five vehicles side by side. Then you’ll see not only battery, range, consumption, AC and DC charging power, average charging power, charging time, energy charged, and costs, but also a suitable or similar internal combustion engine vehicle for comparison. This is particularly exciting to me because it means you’re no longer just looking at a single vehicle. You can see right away how differently vehicles react, even when using the same parameters. One car might have a larger battery but charge more slowly. Another has less capacity but is more efficient. Yet another charges particularly quickly in the first fifteen minutes. These are exactly the kinds of differences I wanted to highlight.
The Pro label is currently more of a placeholder and structural element than a strict paywall. I intentionally included these features early on because I wanted to see where VoltSim could go. For now, I don’t want to simply hide the tool behind a paywall. There’s the idea of “buying a coffee” at the top, and that’s exactly what fits the project better right now. Anyone who finds VoltSim useful or wants to support its development should be able to give me a voluntary contribution. There will be a PayPal link or a simple way to support the project for this purpose. I still need to decide exactly what the monetization will look like later on. It’s more important to me that the tool works for now, can be tried out, and grows as a project.
Another area that was important to me is the used car mode with battery health. Especially with used electric cars, it’s not just the original battery capacity that matters, but the State of Health. If a vehicle once had a certain usable capacity according to the spec sheet, but the battery now only reaches sixty, seventy, or eighty percent of that, it significantly changes the equation. In the screenshot, you can see that you can set an SOH value. This results in a reduced usable capacity, and the simulation can show how this affects charging time, range, and the curve. This is also intended as a Pro feature, but is currently more of a work-in-progress. I find the feature exciting because it makes VoltSim more interesting not only for new cars but also for used cars.
I deliberately divided the frontend into individual applets or control areas. There is the vehicle configuration, the simulation, the charging curve, the time limit section, the cost comparison, the payback period, and the vehicle comparison. I built and iterated on the UI using Replit, while the actual logic behind it was the core of the project for me. ChatGPT mainly helped me structure vehicle data, categorize variants, and make the sheer volume of models manageable. But the actual question, the computational logic, and the structure of the tool came from my observations and from the desire to make this very problem visible.
For me, VoltSim is therefore not a typical comparison portal in the traditional sense. It’s more of a testing ground. You can select a car, play around with charging power, change the starting and target charge levels, compare AC and DC, test temperatures, account for preconditioning, simulate a used battery, compare costs, and ultimately see how all of this plays out. It’s not about presenting a definitive truth. It’s about making assumptions visible. If someone says an electric shuttle could never work in everyday production, with VoltSim you can at least say: Let’s take a look. What’s the runtime? Which charging station would be accessible? Which vehicle are we even talking about? And how much energy would be recovered within that window?
That’s also why the simulator fits so well with the original film set story for me. I didn’t want to just counter the classic diesel defenders with a soundbite. I didn’t want to say, “You’re wrong.” I wanted to build a tool that shows: there could be another way. Maybe not everywhere. Maybe not on every set. Maybe not for every vehicle. But in many urban or suburban situations, the question is at least valid. If shuttles are sitting around anyway, if charging points are within reach, and if a small fleet is organized intelligently, then electric isn’t automatically unrealistic.
Of course, VoltSim doesn’t replace real fleet management. It doesn’t tell which driver needs to go where and when. It doesn’t account for spontaneous production changes, road closures, delays on set, or frantic production managers who suddenly need five vehicles at once. But it can make the technical part of the question easier to understand. It can show whether a vehicle recharges enough within a specific time window, whether a short stop is even relevant, and how big the difference between different models can be.
That was exactly the second step following the original idea. First came the observation: Diesel shuttles sit idle longer than you’d think. Then came the question: Could this idle time be charging time? And then came VoltSim as an attempt not only to discuss this question theoretically, but to make it visible in practice. The EV charging simulator isn’t finished yet and will probably never be finished in that sense, because new vehicles, new variants, and new ideas are always being added. But it’s now at a point where you can see the basic idea. You can set a scenario, select a vehicle, look at the graph, compare costs, and check whether your gut feeling actually matches the numbers.
And that’s exactly what I was after. Not a perfect answer. Not a tool that ends every discussion. But a little bit more reality in a debate that’s often conducted in far too general terms.
Try Out VoltSim HERE
