Once again Gurtam proves that the best is not the enemy of the good. Half a year ago we updated the proprietary fuel consumption calculation algorithm to offer Wialon users a more flexible, precise, and efficient solution.In today’s article, we will tell about how our partners live with the new opportunities, how they deliver never yet seen projects and how they are doing great without FLS (Fuel level sensor) just relying on simple Math and their own mind flexibility.
Until March Wialon Hosting update, there were two ways to identify fuel consumption: by rates and by math. In the first case, to get the result you needed to multiply the rate by mileage. For instance, multiply 30 liters by 500 km that the trucker covered in a day. In the second case, you needed to take idling, urban, and suburban fuel consumption rates into consideration. It is simple for those who don’t care about accuracy but only about the drivers to fit in the rates by any means.
After the update, fuel consumption module was enhanced and became more flexible due to the use of engine efficiency sensors. They allow to set an individual consumption value with different load (by rpm) and under special circumstances (for example, machinery movement through a thick snow layer).
Initially, this innovation caused much discussion. But with the course of time, a new calculation method proved to be highly efficient. Later, in “Advanced” tab, we implemented the function similar to that of the calculation by rates. But it was done more for the sake of an end-user not always eager to see into the technical issues. Among those updates that were introduced to make the work easier were:
“Navigator” LLC, our partner from the Russian Federation, highly appreciated the new “Fuel Consumption” module functionality. They developed a seasonal coefficient calculator and came up with the formula of fuel consumption calculation by speed and without FLS or other sensors. To prove the efficiency of the new algorithm, the company carried out a comparative study of fuel consumption by math and engine efficiency sensor that emulated FLS.Initial data:
The rate of 30 liters per 100 km turned out to be true only at 60 km speed. Actual consumption was different depending on the speed:
In our partner’s example, a heavy truck covered 12.2% of the distance at speed less than 60 km/h, and average consumption by FLS was 32.53 liters per 100 km.
Now we have to enter this data into the system. We create engine efficiency sensor with “speed” parameter and open a calculation table. By working with XY pairs we enter the appropriate speed intervals in X column. In Y column we enter the coefficient instead of the rate. Its calculation formula was tested out:
Y=((rate l/100 km/(100/km/h speed))/2)*(1.6/idling run rate l/h), where 1.6 is an additional coefficient for Scania trucks idling run rate.
To calculate Y you can use the calculator that was developed by our partner.
For example, if the rate is 5 l/h, we get this table with coefficients for different speed intervals.
Knowing the idling rate for Scania heavy trucks, we applied this configuration to other units of the same heavy truck modification and got the following result:
It is almost identical to the one we got with FLS. If we use this formula for other trucks rates, we can calculate consumption without fuel level and other sensors. And it is just by speed! Any number of sensors can be added while using this calculation mechanism. For instance:
It all provides precise fuel consumption control even without FLS.
Now let’s talk about how to solve previously unmanageable issues using FLS. The client deals with oil-well drilling. His machinery appears at the needed location where it is being filled. After the work is finished, the fuel gets dumped and the machinery moves to another location. The issue was that the fuel consumption rate of such machinery was 300 liters per hour but the fuel was dumped at 150 liters per hour and at a killed engine. This fact made it impossible to display thefts that were automatically put into “Consumed by FLS” statistics section because the consumption was within the specified range regardless the engine not working. The client was not happy about it. The issue of course was solved before the update. But let’s compare the solution before and after it. As we call it, feel the difference!
With a new fuel control algorithm we got rid of the “crutches”: we managed to eliminate several already unnecessary validator sensors (speed, engine ignition) and to create an engine efficiency sensor “Machinery engine hours” using a single consumption rate coefficient without the need to set the consumption rate for each individual sensor. Multiplying the rate by coefficient we get an on-load consumption.
On top of that, due to the option of putting the rate for the work of an engine under different load into the “Engine hours” table, it is easy to add the “Consumed by rate” column with a view to “rate*time” regardless the movement.
Previously, to do that you created:
… and then made a “Consumed by instant fuel consumption sensor” column and renamed it into “Consumed by rates”, i.e. how much fuel was spent for these seconds between the messages. See how much of extra work you don’t do now?
All these allowed to considerably reduce the number of custom sensors and therefore to spend less time on configuring and to reduce the error probability.
So, having used new options we got:
Therefore, we are not always wrong when replacing an old handy and popular function with a new one. For the first 6 months of a new calculation method usage, it proved to be 100% efficient. And it was confirmed by both integrators and their clients.
Our module allows to:
According to Gurtam partners, Wialon usage helps to save up to 15% of fuel and to reduce thefts by 90%. The system introduction pays off in 3-4 months. Such monitoring has proven to discipline drivers and to effectively plan the motor park work. Gurtam own calculation algorithm, the possibility to get full analytics and to monitor fuel level in real time make Wialon a head higher than similar programs.
We appreciate your contribution to Wialon development and thank you for your support. Together we will make Wialon even better. Share your experience with us at firstname.lastname@example.org so that we could publish it on our blog.