I mean: in my case, I'm talking about trucks payload. So, knowing data about the engine usage (gear, torque) of a truck driving along a certain road (of which are known the characteristics); is it possible to estimate the payload of the truck during its journey?
I am analyzing data about truck fleet fuel consumption and I would like to consider negligible the effect of the payload on the trucks. If I could estimate the payload of the truck during its journey I would compare just data about trucks traveling in similar conditions. Do you know any possible way which would permit me to estimate it? Can you suggest me any publication about similar studies (for trucks but for airplanes or for trains also)?
Its possible, but the achieveable accuracy of estimation strongly depends on the tolerance of data mining. Longitodinal vehicle dynamics is influenced by propulsion forces, braking forces, air drag, rolling resistance, and road inclination, as well as the translational & rotational moments of inertia (e.g. see the publication attached). Challenge for an accurate estimation is the sourcing of dynamically changing factors in this equation.
Kind regards,
Mario
Conference Paper Basics of longitudinal vehicle dynamics
Thank you very much Dr Hirz! I'll have a look to your publication immediately.
Any other contribution is welcome.
I know that the Swedish Truck manufacturer Scania is currently testing a system where they use Newton’s second law to estimate weight. Personally, this is not my expertise but I if I understood them right you can estimate the weight by using the acceleration and retardation between gear-shifts.
Hopefully this might help you a bit
Henrik
If you have torque M and the gear (and, of course, the speed v), you can calculate the engine speed f (rotations per second) and from that the instantaneous mechanical power P=2*pi*M*f
The instantaneous mechanical power is composed of following main contributions (see Chapter 20.4 of "Traffic Flow Dynamics", Springer, 2013):
P=P0+v*F=P0+v*[m*g*(mu+mu1*v+alpha+m'*acc)+C_air*v^2]
with mu and mu1 being friction coefficients, acc the acceleration, alpha the road gradien, and C_air containing truck geometry parameters and the air-drag coefficient
In order to eliminate the confounding (and possibly nonconstant) parameters P0, mu, mu1, and C_air, one could pick portions of the trajectories with the same speed but different accelerations to determine the dynamic mass m' (which is connected to m by known relations), or portions with the same speed but different gradients which gives directly m.
In any case, the gradient must be known for this. Otherwise, the analysis becomes more complex.
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