Precise, mass-based range prediction for commercial electric vehicles
Precise battery range prediction is crucial for electric delivery vehicles, however their driving range varies with transported mass. Discover how our software-based solution can help.
What determines the driving range of an electric vehicle (EV)?
A variety of electric light trucks for last mile delivery are available on the market. Their typical driving range is somewhere around 150 – 200 miles (roughly 250 – 300 kilometers). The effective battery range of each vehicle depends very much on factors like:
- Equipment manufacturer and vehicle model
- Battery health status
- Driving style
- Environmental conditions, and
- Vehicle mass.
General vehicle data are fixed, and many other data can be monitored via telematics solutions (speed, outside temperature, …) but not the loaded mass, which has an huge impact on the actual range. You cannot roll a small delivery truck over a scale at every stop, nor can you type this data manually into its onboard computer.
While the availability of charging stations is mainly a concern for private electric car owners, range anxiety remains a significant barrier to large-scale use of battery electric vehicles (BEVs) in commercial fleets. The issue is not just about the nominal range of an electric utility vehicle rolling off a production plant, but rather the actual result how it behaves in your day-to-day business, about your expectations with respect to charging frequency, and most important of all: reliable battery range prediction whatever payload has been picked up at a stock or warehouse.
Why precise range prediction matters for delivery fleets
Constant changes in the transported vehicle mass are inherent to last mile delivery services, but the loaded mass reduces the remaining driving range. This makes driving range prediction of commercial electric vehicles so difficult. Currently, electric vehicles and electric trucks do not have the ability to measure their own instantaneous mass. The predicted battery state of charge (SOC), which is sometimes displayed on the instrument panel, is based on energy consumption history, not on transported mass.
Under constant cost pressure, each delivery company is searching for means to optimize fleet operation, including the number of deliveries with one single charge. If the remaining electric vehicle range is not well predicted, there is a risk that a last mile delivery truck runs out of battery during operation. Unplanned breakdowns disorganize the fleet planning, lead to additional costs and customer dissatisfaction. Range anxiety is a limit to the number of trips before charging, and has a direct impact on operations efficiency. Fleet professionals need reliable driving range data for efficient use of BEVs.
Under constant cost pressure, each delivery company is searching for means to optimize fleet operation, including the number of deliveries with one single charge. If the remaining electric vehicle range is not well predicted, there is a risk that a last mile delivery truck runs out of battery during operation.
Unplanned breakdowns disorganize the fleet planning, lead to additional costs and customer dissatisfaction. Range anxiety is a limit to the number of trips before charging, and has a direct impact on operations efficiency. Fleet professionals need reliable driving range data for efficient use of BEVs.
How we predict electric car/truck range
COMPREDICT has developed innovative products based on machine learning. Our company’s
virtual sensors based on standard CAN bus signals are able to calculate instantaneous vehicle mass with a precision better than +/-5%, after 2-5 minutes city driving. Newly added vehicles are automatically parameterized in the
software during the first half-hour of usage, using on-board signals as training data.
Read more about how our online vehicle mass measurement works.
With the loaded vehicle mass as input, reliable battery range prediction is possible for electric vehicles. This allows that during a working day, every single electric vehicle will return to a safe charging point before the battery
state-of-charge (SOC) is too low.
Benefits from precise range prediction of electric vehicles
Our solution provides a competitive advantage to fleet managers using battery electric vehicles (BEVs):
- Reliable, instantaneous vehicle mass at a precision of +/-5%.
- Easy integration into existing telematics solution.
- Automatic setup of new vehicles.
- Eliminate range anxiety.
- Increased customer satisfaction.
What else do we offer to increase revenue and operational efficiency of fleets?
Our virtual sensors predict fatigue and failure of other electrical and mechanical vehicle components like tires and brakes. Shifting unplanned service interventions to planned maintenance increases the rate of actual use of BEVs, and paves the ways for an increase in the revenue generated by a fleet.
Virtual sensors alert about brake system anomalies and thus reduce risks for your drivers significantly.
Read more about all-in-one electric vehicle monitoring with virtual sensors.
Do you operate a significant fleet of vehicles? Let’s discuss!
+49 (0)6151 3844614
64283 Darmstadt, Germany