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Research Papers

Adaptive Control of a Piezoelectric Valve for Fluid-Borne Noise Reduction in a Hydraulic Buck Converter

[+] Author and Article Information
Min Pan

Department of Mechanical Engineering,
Centre for Power Transmission and
Motion Control,
University of Bath,
Bath BA2 7AY, UK
e-mail: m.pan@bath.ac.uk

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received September 19, 2016; final manuscript received December 20, 2016; published online May 24, 2017. Assoc. Editor: Dumitru I. Caruntu.

J. Dyn. Sys., Meas., Control 139(8), 081007 (May 24, 2017) (12 pages) Paper No: DS-16-1450; doi: 10.1115/1.4035613 History: Received September 19, 2016; Revised December 20, 2016

The hydraulic buck converter (HBC) is a novel high-bandwidth and energy-efficient device which can adjust or control flow and pressure by a means that does not rely on throttling the flow and dissipation of power. However, the nature of a HBC can cause severe fluid-borne noise (FBN), which is the unsteady pressure or flow in the fluid-filled hydraulic circuit. This is due to the operation nature of a high-speed switching valve of the device. The FBN creates fluctuating forces on the pipes which lead to system structure-borne noise that develops air-borne noise reaching to 85 dB. Thus, there is a need for an effective method that does not impair the system performance and efficiency to reduce the FBN. This paper describes the first investigation of an active controller for FBN cancellation in a HBC based on in-series and by-pass structures. The dynamics and the noise problem of the HBC are investigated using the analytical models. A piezoelectrically actuated hydraulic valve with a fast response and high force is applied as the adaptive FBN attenuator. The performance and robustness of the designed noise controller were studied with different operating conditions of a HBC. Simulated and experimental results show that excellent noise cancellation (30 dB) was achieved. The proposed active attenuator is a very promising solution for FBN attenuation in modern digital hydraulic systems which promise high energy efficiency but suffer severe noise or vibration problems in practice.

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Figures

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Fig. 6

Implementation of the narrowband feedforward FXLMS algorithm on a HBC

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Fig. 5

Block diagram of ANC system using the FXLMS algorithm [27]

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Fig. 4

Predicted dynamic flow rate using a HBC analytical model

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Fig. 3

Idealized operation of flow booster [24]

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Fig. 2

Circuit of a three-port HBC

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Fig. 1

Electrical circuit of a buck converter

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Fig. 10

Schematic of the FBN cancellation structures for a HBC: (a) by-pass structure and (b) in-series structure

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Fig. 7

Multiple-frequency ANC system using FXLMS algorithm in parallel

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Fig. 8

Schematic cross section of the piezoelectrically actuated valve [21,30]

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Fig. 9

Steady-state characteristics for the piezoelectric valve with an applied voltage of 400 V

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Fig. 13

Frequency response of secondary path using FBLMS online identification technique with a by-pass structure

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Fig. 19

Experimental test rig with the by-pass structure: (a) Schematic of the experimental test rig with the by-pass structure and (b) test rig

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Fig. 20

Frequency response of secondary path at the different working seconds with a by-pass structure

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Fig. 14

Multiple harmonics cancellation of FBN using FBLMS online technique with a by-pass structure

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Fig. 18

Simulated filter tap weights w1 and w2 of the subcontrollers with an in-series structure

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Fig. 15

Simulated filter tap weights w1 and w2 of the subcontrollers with a by-pass structure

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Fig. 16

Frequency response of secondary path using FBLMS online identification technique with an in-series structure

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Fig. 11

Simulated FBN generated from a HBC with different sizes of accumulator

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Fig. 12

Frequency response of an HBC with an accumulator volume of 2 L and 0.02 L

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Fig. 17

Multiple harmonics cancellation of FBN using FBLMS online technique with an in-series structure

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Fig. 21

Multiple harmonics cancellation using FBLMS online identification technique with a by-pass structure

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Fig. 22

Experimental filter tap weights w1 and w2 of the subcontrollers

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Fig. 23

Experimental test rig with the in-series structure: (a) Schematic of the experimental test rig with the in-series structure and (b) test rig

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Fig. 24

Frequency response of secondary path at the different working seconds with an in-series structure

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Fig. 25

Multiple harmonics cancellation of FBN using FBLMS online technique with an in-series structure

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Fig. 26

Experimental filter tap weights w1 and w2 of the subcontrollers with an in-series structure

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