Dielectric elastomer Generator(s) (DEG) are highly suited to harvesting from environmental sources because they are
light weight, low cost, and can be coupled directly to rectilinear motions and harvest energy efficiently over a wide
frequency range. Because of these benefits, simple and low cost generators could be enabled using DEG.
Electrical energy is produced on relaxation of a stretched, charged DEG: like-charges are compressed together and
opposite-charges are pushed apart, resulting in an increased voltage. The manner in which the DEG charge state is
controlled greatly influences the amount of energy that is produced. For instance, the highest energy density ever
demonstrated for DEG is 550 mJ/g, whereas the theoretical energy density of DEG has been reported as high as 1700
mJ/g if driven close to their failure limits.
The discrepancy between realised and theoretical energy production highlights that large performance gains can be
achieved through smarter charge control that drives the generator close to its failure limits. To do so safely, we need to
be able to monitor the real-time electromechanical state of the DEG. This paper discusses the potential of self-sensing
for providing feedback on the generator’s electromechanical state. Then we discuss our capacitive self-sensing method
which we have demonstrated to track the displacement of a Danfoss Polypower generator as it was cyclically stretched
and harvested energy.
Sensing motion of the human body is a difficult task. From an engineers’ perspective people are soft highly mobile
objects that move in and out of complex environments. As well as the technical challenge of sensing, concepts such as
comfort, social intrusion, usability, and aesthetics are paramount in determining whether someone will adopt a sensing
solution or not.
At the same time the demands for human body motion sensing are growing fast. Athletes want feedback on posture and
technique, consumers need new ways to interact with augmented reality devices, and healthcare providers wish to track
recovery of a patient.
Dielectric elastomer stretch sensors are ideal for bridging this gap. They are soft, flexible, and precise. They are low
power, lightweight, and can be easily mounted on the body or embedded into clothing. From a commercialisation point
of view stretch sensing is easier than actuation or generation - such sensors can be low voltage and integrated with
conventional microelectronics.
This paper takes a birds-eye view of the use of these sensors to measure human body motion. A holistic description of
sensor operation and guidelines for sensor design will be presented to help technologists and developers in the space.
Being able to accurately record body motion allows complex movements to be characterised and studied. This is especially important in the film or sport coaching industry. Unfortunately, the human body has over 600 skeletal muscles, giving rise to multiple degrees of freedom. In order to accurately capture motion such as hand gestures, elbow or knee flexion and extension, vast numbers of sensors are required. Dielectric elastomer (DE) sensors are an emerging class of electroactive polymer (EAP) that is soft, lightweight and compliant. These characteristics are ideal for a motion capture suit. One challenge is to design sensing electronics that can simultaneously measure multiple sensors. This paper describes a scalable capacitive sensing device that can measure up to 8 different sensors with an update rate of 20Hz.
We report on the use of capacitive self-sensing to operate a DEA-based tunable grating in closed-loop mode. Due to their large strain capabilities, DEAs are key candidates for tunable optics applications. However, the viscoelasticity of elastomers is detrimental for applications that require long-term stability, such as tunable gratings and lenses. We show that capacitive sensing of the electrode strain can be used to suppress the strain drift and increase the response speed of silicone-based actuators. On the other hand, VHB actuators exhibit a time-dependent permittivity, which causes a drift between the device capacitance and its strain.
Manipulators based on rigid, kinematically constrained structures and highly geared electromagnetic actuators are poorly
suited in applications where objects are soft, delicate, or have an irregular shape, especially if they operate outside of the
highly structured environment of a factory. Intrinsically soft DEA, imparted with the ability to self-sense enable the
creation of soft, smart artificial muscles provide a way forward. Inherent compliance simplifies manipulator trajectory
planning and force control, enables the manipulator to conform to the object, and provides natural damping of
mechanical disturbances. In this paper we present a simple proof-of-concept building block that could be used to create a
compliant DEA-based manipulator with self-sensing feedback. Capacitive self-sensing has been used to both detect
when contact is made with an object and gather information about the object's stiffness. Integrated into a manipulator,
this information could be used to adjust the grip directly, or used to reposition or reorient the manipulator to achieve a
desired grasp.
Unlike electromagnetic actuators, Dielectric Elastomer Actuators (DEAs) can exert a static holding force without
consuming a significant amount of power. This is because DEAs are electrostatic actuators where the electric charges
exert a Maxwell stress. A charged DEA stores its electrical energy as potential energy, in a similar way to a capacitor. To
remove or reduce the Maxwell stress, the stored charge with its associated electrical energy must be removed. Current
DEA driver electronics simply dispose of this stored electrical energy. If this energy can be recovered, the efficiency of
DEAs would improve greatly. We present a simple and efficient way of re-using this stored energy by directly
transferring the energy stored in one DEA to another. An energy transfer efficiency of approximately 85% has been
achieved.
To reduce the likelihood of ventilator induced lung injury a neonatal lung simulator is developed based on Dielectric
Elastomer Actuators (DEAs). DEAs are particularly suited for this application due to their natural like response as well
as their self-sensing ability. By actively controlling the DEA, the pressure and volume inside the lung simulator can be
controlled giving rise to active compliance control. Additionally the capacitance of the DEA can be used as a
measurement of volume eliminating the integration errors that plague flow sensors.
Based on simulations conducted with the FEA package ABAQUS and experimental data, the characteristics of the lung
simulator were explored. A relationship between volume and capacitance was derived based on the self sensing of a
bubble actuator. This was then used to calculate the compliance of the experimental bubble actuator. The current results
are promising and show that mimicking a neonatal lung with DEAs may be possible.
We use our thumbs and forefingers to rotate an object such as a control knob on a stereo system by
moving our finger relative to our thumb. Motion is imparted without sliding and in a precise manner. In
this paper we demonstrate how an artificial muscle membrane can be used to mimic this action. This is
achieved by embedding a soft gear within the membrane. Deformation of the membrane results in
deformation of the polymer gear and this can be used for motor actuation by rotating the shaft.
The soft motors were fabricated from 3M VHB4905 membranes 0.5mm thick that were pre-stretched
equibiaxially to a final thickness of 31 μm. Each membrane had polymer acrylic soft gears inserted at
the center. Sectors of each membrane (60° sector) were painted on both sides with conducting carbon
grease leaving gaps between adjoining sectors to avoid arcing between them. Each sector was
electrically connected to a power supply electrode on the rigid acrylic frame via narrow avenues of
carbon-grease. The motors were supported in rigid acrylic frames aligned concentrically. A flexible
shaft was inserted through both gears. Membranes were charged using a step wave PWM voltage
signal delivered using a Biomimetics Lab EAP Control unit. Both membrane viscoelasticity and the
resisting torque on the shaft influence motor speed by changing the effective circumference of the
flexible gear.
This new soft motor opens the door to artificial muscle machines molded as a single part.
Sensing the electrical characteristics of a Dielectric Elastomer Actuator(s) (DEA) during actuation is critical to
improving their accuracy and reliability. We have created a self-sensing system for measuring the equivalent series
resistance of the electrodes, leakage current through the equivalent parallel resistance of the dielectric membrane, and the
capacitance of the DEA whilst it is being actuated. This system uses Pulse Width Modulation (PWM) to simultaneously
generate an actuation voltage and a periodic oscillation that enables the electrical characteristics of the DEA to be
sensed. This system has been specifically targeted towards low-power, portable devices. In this paper we experimentally
validate the self-sensing approach, and present a simple demonstration of closed loop control of the area of an expanding
dot DEA using capacitance feedback.
Dielectric breakdown often leads to catastrophic failure in Dielectric Elastomer Actuator(s) (DEA). The resultant
damage to the dielectric membrane renders the DEA useless for future actuation, and in extreme cases the sudden
discharge of energy during breakdown can present a serious fire risk. The breakdown strength of DEA however is
heavily dependent on the presence of microscopic defects in the membrane giving its overall breakdown strength
inherent variability. The practical consequence is that DEA normally have to be operated far below their maximum
performance in order to achieve consistent reliability.
Predicting when DEA are about to suffer breakdown based on feedback will enable significant increase in effective DEA
performance without sacrificing reliability. It has been previously suggested that changes in the leakage current can be a
harbinger of dielectric breakdown; leakage current exhibits a sharp increase during breakdown. In this paper the
relationship between electric field and leakage current is investigated for simple VHB4905-based DEA. Particular
emphasis is placed on the behaviour of leakage current leading up to and during breakdown conditions. For a sample size
of nine expanding dot DEA, the DEA that failed at electric fields below the maximum tested exhibited noticeably higher
nominal power dissipation and a higher frequency of partial discharge events than the DEA that did not breakdown
during testing. This effect could easily be seen at electric fields well below that at which the worst performing DEA
failed.
Arrays of actuators are ubiquitous in nature for manipulation, pumping and propulsion. Often these arrays are
coordinated in a multi-level fashion with distributed sensing and feedback manipulated by higher level controllers. In
this paper we present a biologically inspired multi-level control strategy and apply it to control an array of Dielectric
Elastomer Actuators (DEA). A test array was designed consisting of three DEA arranged to tilt a set of rails on which a
ball rolls. At the local level the DEA were controlled using capacitive self-sensing state machines that switched the
actuator off and on when capacitive thresholds were exceeded, resulting in the steady rolling of the ball around the rails.
By varying the voltage of the actuators in the on state, it was possible to control the speed of the ball to match a set point.
A simple integral derivative controller was used to do this and an observer law was formulated to track the speed of the
ball.
The array demonstrated the ability to self start, roll the ball in either direction, and run at a range of speeds determined by
the maximum applied voltage. The integral derivative controller successfully tracked a square wave set point. Whilst the
test application could have been controlled with a classic centralised controller, the real benefit of the multi-level strategy
becomes apparent when applied to larger arrays and biomimetic applications that are ideal for DEA. Three such
applications are discussed; a robotic heart, a peristaltic pump and a ctenophore inspired propulsion array.
Ctenophores or "comb jellies" are small sea creatures that propel themselves with rows of ciliated bending actuators or
'paddles'. In some species the actuators are coordinated via mechano-sensitivity; the physical contact of one paddle
triggers the motion of the next resulting in a wave of activation along the row. We seek to replicate this coordination
with an array of capacitive self-sensing Dielectric Elastomer Minimum Energy Structure(s) (DEMES) bending actuators.
For simplicity we focused on a conveyor application in air where four DEMES were used to roll cylindrical loads along
some rails. Such a system can automatically adjust to changing load dynamics and requires very little computational
overhead to achieve coordination.
We used a finite element modelling approach for DEMES development. The model used a hybrid Arruda-Boyce strain
energy function augmented with an electrostatic energy density term to describe the DEA behaviour. This allowed the
use of computationally efficient membrane elements giving simulation times of approximately 15 minutes and thus rapid
design development. Criteria addressing failure modes, the equilibrium state, and stroke of the actuators were developed.
The model had difficulty in capturing torsional instability in the frame thus design for this was conducted
experimentally.
The array was built and successfully propelled teflon and brass rollers up an incline. Noise in the capacitive sensor
limited the sensitivity of the actuators however with PCB circuit fabrication this problem should be solved.
We describe a low profile and lightweight membrane rotary motor based on the dielectric elastomer actuator (DEA). In
this motor phased actuation of electroded sectors of the motor membrane imparts orbital motion to a central gear that
meshes with the rotor.
Two motors were fabricated: a three phase and four phase with three electroded sectors (120°/sector) and four sectors
(90°/sector) respectively. Square segments of 3M VHB4905 tape were stretched equibiaxially to 16 times their original
area and each was attached to a rigid circular frame. Electroded sectors were actuated with square wave voltages up to
2.5kV. Torque/power characteristics were measured. Contactless orbiter displacements, measured with the rotor
removed, were compared with simulation data calculated using a finite element model.
A measured specific power of approximately 8mW/g (based on the DEA membrane weight), on one motor compares
well with another motor technology. When the mass of the frame was included a peak specific power of 0.022mW/g was
calculated. We expect that motor performance can be substantially improved by using a multilayer DEA configuration,
enabling the delivery of direct drive high torques at low speeds for a range of applications.
The motor is inherently scalable, flexible, flat, silent in operation, amenable to deposition-based manufacturing
approaches, and uses relatively inexpensive materials.
The excellent overall performance and compliant nature of Dielectric Elastomer Actuators (DEAs) make them ideal
candidates for artificial muscles. Natural muscle however is much more than just an actuator, it provides position
feedback to the brain that is essential for the body to maintain balance and correct posture. If DEAs are to truly earn the
moniker of "artificial muscles" they need to be able to reproduce, if not improve on, this functionality.
Self-sensing DEAs are the ideal solution to this problem. This paper presents a system by which the capacitance of a
DEA can be sensed while it is being actuated and used for feedback control. This system has been strongly influenced by
the desire for portability i.e. designed for use in a battery operated microcontroller based system. It is capable of
controlling multiple independent DEAs using a single high voltage power supply. These features are important
developments for artificial muscle devices where accuracy and low mass are important e.g. a prosthetic hand or force-feedback
surgical tools.
A numerical model of the electrical behaviour of the DEA that incorporates arbitrary leakage currents and the impact of
arbitrary variable capacitance has been created to model a DEA system. A robust capacitive self-sensing method that
uses a slew-rate controlled Pulse Width Modulation (PWM) signal and compensates for the effects of leakage current
and variable capacitance is presented. The numerical model is then used to compare the performance of this new method
with an earlier method previously published by the authors.
KEYWORDS: Microsoft Foundation Class Library, Capacitors, Electrodes, Robots, Artificial muscles, Actuators, Polymers, Capacitance, Composites, Electrons
We consider the embodiment of a microbial fuel cell using artificial muscle actuators. The microbial fuel cell digests
organic matter and generates electricity. This energy is stored in a capacitor bank until it is discharged to power one of
two complimentary artificial muscle technologies: the dielectric elastomer actuator and the ionic-polymer metal
composite. We study the ability of the fuel cell to generate useful actuation and consider appropriate configurations to
maximally exploit both of these artificial muscle technologies. A prototype artificial sphincter is implemented using a
dielectric elastomer actuator. Stirrer and cilia mechanisms motivate experimentation using ionic polymer metal
composite actuators. The ability of the fuel cell to drive both of these technologies opens up new possibilities for truly
biomimetic soft artificial robotic organisms.
The future of Dielectric Elastomer Actuator (DEA) technology lies in miniaturizing individual elements and utilizing
them in array configurations, thereby increasing system fault tolerance and reducing operating voltages. An important
direction of DEA research therefore is real-time closed loop control of arrays of DEAs, particularly where multiple
degrees-of-freedom are desirable.
As the number of degrees-of-freedom increases a distributed control system offers a number of advantages with respect
to speed and efficiency. A low bandwidth digital control method for DEA devices is presented in this paper. Pulse Width
Modulation (PWM) is used as the basis for a current controlled DEA system that allows multiple degrees-of-freedom to
be controlled independently and in parallel using a single power supply set to a fixed voltage. The amplitude and the
duty cycle of the PWM signal control the current flow through a high speed, high voltage opto-coupler connected in
series with a DEA, enabling continuous control of both the output displacement and speed. Controlling the current in
real-time results in a system approaching a stable and robust constant charge system.
Closed loop control is achieved by measuring the rate of change of the voltage across the DEA in response to a step
change in the current input generated by the control signal. This enables the capacitance to be calculated, which in
combination with the voltage difference between the electrodes and the initial dimensions, enables the charge, strain state
and Maxwell pressure to be inferred. Future developments include integrating feedback information directly with the
control signal, leaving the controller to coordinate rather than control individual degrees-of-freedom.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.