In working machines like wheel loaders the human operator is essential for the performance of the total system. Productivity and energy efficiency are both dependent not only on inherent machine properties and working place conditions, but also on how the operator manoeuvres the machine. In order to operate energy-efficient the operator has to experience the machine as harmonic. This is important to consider during the development of such working machines. The influence of the human operator is an aspect that is traditionally neglected in dynamic simulations conducted in concept design, because the modelling needs to be extended beyond the technical system. In the research presented in this paper we show two approaches to rule-based simulation models of a wheel loader operator. Both operator models interact with the machine model just as a human operator does with the actual machine. It is demonstrated that both operator models are able to adapt to basic variations in workplace setup and machine capability. A "human element" can thus be introduced into dynamic simulations of working machines, providing more relevant answers with respect to operator-influenced complete-machine properties such as productivity and energy efficiency. Operability of a machine is traditionally evaluated by professional test operators using physical prototypes. The presented research demonstrates how this can be complemented by a calculated measure for the operator’s control effort, derived from the recorded control commands of the machine operator. This control effort measure can also be calculated from the control commands of an operator model in a simulation, such as those presented here. It thus also allows for an assessment of operability already in the concept design phase.

1. Simulating Operability
of Wheel Loaders
Dr. Reno Filla
Volvo Construction Equipment
Emerging Technologies

3. Making working machines
more energy-efficient
and easier to operate
...by:
1. understanding the machine as one system
2. understanding the interaction between
machine, operator and working environment

5. Business idea for the OEM
Find perfect balance
Design machines with a natural,
workload-minimising way to operate
with
• productivity as high as required
• energy efficiency as high as possible
Give assistance to the operator if needed
(guidance).
Focus: Conceptual Design phase

6. Product Development
Concept design
Concept evaluation
Productivity
Energy efficiency
Operability

7. Concept evaluation
Productivity
Energy efficiency
Operability
Early days of simulation:
We were lacking the operator
and the working environment

8. Operator model Rules
Discrete-event approach (finite state machine) gained in
interviews

9. Operator model Rules
Discrete-event approach (finite state machine) gained in
 interviews
 







Extension from V- to Y-cycle

10. Operator model Rules
Discrete-event approach (finite state machine) gained in
interviews
Some rules for bucket filling:
• Accelerate to certain initial velocity
• Shift to 1st gear when bucket in gravel
• Lift somewhat
• Keep advancing
• When wheel about to slip:
less gas pedal value and start lifting
• When lift pressure > max: tilt backward

11. Operator model Rules
Discrete-event approach (finite state machine) gained in
interviews


12. Operator model Rules
Discrete-event approach (finite state machine) gained in
interviews

13. Operator model
Discrete-event approach (finite state machine)

14. Operator model
useful for simulation of
• Productivity and
• Energy efficiency (fuel consumption)

16. Operator workload study
18 operators with varying skill (from inexperienced to expert)
performed bucket loading with a wheel loader
• 3 settings where traction force was limited via software
• …which has a heavy impact on ease of bucket filling
with following data acquired
• data from CAN bus and external sensors
• video
• self-evaluations on machine and own performance

17. Operator workload study
Hypothesis:
• The control commands of the operator (control effort)
are indicative of the machine’s operability (in bucket loading)
• Higher use of operator controls indicates higher workload
and thus lower operability
Human operator’s
use of machine
controls
Human operator’s
perception of
machine’s operability
Operator model’s
use of machine
controls

18. Operator workload study
Hypothesis:
• The control commands of the operator (control effort)
are indicative of the machine’s operability (in bucket loading)
• Higher use of operator controls indicates higher workload
and thus lower operability
lift lever
Result:
• Hypothesis confirmed
• Algorithms developed
tilt lever

19. In support of the hypothesis
Strictly monotone relationship 27 22
between control commands
26 28
and ease of bucket fill 12 29 14 25
Monotone relationship 20
08
06
Operator skill
0 25 50 75 100
Neutral (constant) 04 11
None-monotone 21
13
relationship 02
Inverse relationship 18 05
Load-normalized Control effort with “Split & Merge” algorithm, arithmetic sum

20. Product Development
Concept design
Concept evaluation
Productivity
Operator models Energy efficiency
Control effort measure Operability

21. Product Development
Concept design

22. Thank you!
Ideas, comments or questions?
reno.filla@volvo.com