TY - JOUR
T1 - Torque estimation in marine propulsion systems
AU - Manngård, Mikael
AU - Koene, Ivar
AU - Lund, Wictor
AU - Haikonen, Sampo
AU - Fagerholm, Fredrik A.
AU - Wilczek, Michał
AU - Mnich, Konrad
AU - Keski-Rahkonen, Joni
AU - Viitala, Raine
AU - Björkqvist, Jerker
AU - Toivonen, Hannu T.
N1 - Funding Information:
This work was done within the Business Finland funded research project Reboot IoT Factory. The authors would like to thank the anonymous reviewers for their meticulous reviews and constructive comments, which were of great help to improve the manuscript.
Publisher Copyright:
© 2022 The Authors
PY - 2022/6/1
Y1 - 2022/6/1
N2 - An augmented Kalman filter for torque estimation in marine propulsion-system drive trains is presented. Propeller and motor excitations and torque responses are estimated based on a dynamical model of the system and inboard shaft measurements. Input excitations affecting marine propulsion systems are signals whose statistical properties vary between finite time intervals. Hence, in this paper, excitations are characterized as quasi-stationary signals with bounded power spectral density. Given that upper bounds on the spectral densities are known prior to estimation, it is shown that a linear time-invariant input-and-state observer, minimizing the worst-case power of the estimation errors, can be synthesized by conventional Kalman-filtering techniques. Experiments have been conducted on a laboratory-scale test bench to assess the applicability of the proposed observer for use in marine propulsion systems. The test bench was built to emulate the behavior of a full-scale propulsion system operated in ice and other high load conditions. Estimation results from a full-size underwater mountable azimuthing thruster are also presented. Experiment results show that torque excitations and torque responses at all locations of interest on the engine-propeller drivetrain can be estimated with high accuracy based on a few indirect measurements at convenient locations on the motor shaft.
AB - An augmented Kalman filter for torque estimation in marine propulsion-system drive trains is presented. Propeller and motor excitations and torque responses are estimated based on a dynamical model of the system and inboard shaft measurements. Input excitations affecting marine propulsion systems are signals whose statistical properties vary between finite time intervals. Hence, in this paper, excitations are characterized as quasi-stationary signals with bounded power spectral density. Given that upper bounds on the spectral densities are known prior to estimation, it is shown that a linear time-invariant input-and-state observer, minimizing the worst-case power of the estimation errors, can be synthesized by conventional Kalman-filtering techniques. Experiments have been conducted on a laboratory-scale test bench to assess the applicability of the proposed observer for use in marine propulsion systems. The test bench was built to emulate the behavior of a full-scale propulsion system operated in ice and other high load conditions. Estimation results from a full-size underwater mountable azimuthing thruster are also presented. Experiment results show that torque excitations and torque responses at all locations of interest on the engine-propeller drivetrain can be estimated with high accuracy based on a few indirect measurements at convenient locations on the motor shaft.
KW - Maritime systems
KW - Optimal filtering
KW - Simultaneous input and state estimation
UR - http://www.scopus.com/inward/record.url?scp=85125666447&partnerID=8YFLogxK
U2 - 10.1016/j.ymssp.2022.108969
DO - 10.1016/j.ymssp.2022.108969
M3 - Article
AN - SCOPUS:85125666447
VL - 172
JO - Mechanical Systems and Signal Processing
JF - Mechanical Systems and Signal Processing
SN - 0888-3270
M1 - 108969
ER -