Research Papers

On the Regenerative Capabilities of Electrodynamic Dampers Using Bond Graphs and Model Predictive Control

[+] Author and Article Information
Layne Clemen

Hyundai Center of Excellence in Vehicle
Dynamic Systems and Control,
Department of Mechanical and
Aeronautical Engineering,
University of California,
Davis, CA 95616
e-mail: laclemen@ucdavis.edu

Olugbenga Moses Anubi

GE Global Research Center,
Niskayuna, NY 12309
e-mail: anubimoses@gmail.com

Donald Margolis

Hyundai Center of Excellence in Vehicle
Dynamic Systems and Control,
Department of Mechanical and
Aeronautical Engineering,
University of California,
Davis, CA 95616
e-mail: dlmargolis@ucdavis.edu

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received June 16, 2015; final manuscript received December 14, 2015; published online March 10, 2016. Assoc. Editor: Fu-Cheng Wang.

J. Dyn. Sys., Meas., Control 138(5), 051006 (Mar 10, 2016) (7 pages) Paper No: DS-15-1276; doi: 10.1115/1.4032505 History: Received June 16, 2015; Revised December 14, 2015

There is a constant interest in the performance capabilities of active suspensions without the associated shortcomings of degraded fuel economy. To this effect, electrodynamic dampers are currently being researched as a means to approach the performance of a fully active suspension with minimal or no energy consumption. This paper investigates the regenerative capabilities of these dampers during fully active operation for a range of controller types—emphasizing road holding, ride, and energy regeneration. A model of an electrodynamic suspension is developed using bond graphs. Two model predictive controllers (MPCs) are constructed: standard and frequency-weighted MPCs. The resulting controlled system is subjected to International Organization for Standardization (ISO) roads A–D and the results are presented. For all of the standard MPC weightings, the suspension was able to recover more energy than is required to run the suspension actively. All of the results for optimal energy regeneration occurred on the standard Pareto tradeoff curve for ride comfort and road holding. Frequency weighting the controller increased suspension performance while also regenerating 3–12% more energy than the standard MPC.

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Grahic Jump Location
Fig. 4

Total system bond graph

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Fig. 3

Quarter-car model with electrodynamic damper

Grahic Jump Location
Fig. 2

Electrodynamic actuator bond graph

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Fig. 1

Electrodynamic actuator diagram

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Fig. 6

Ride comfort and road holding projection

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Fig. 7

Frequency-weighted active suspension regenerative capabilities

Grahic Jump Location
Fig. 8

Frequency-weighted ride comfort and road holding projection

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Fig. 5

Electrodynamic damper regenerative capabilities



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