Green,T.C.

Holmes,A.S.

Mitcheson,P.D.

Yates,D.C.

Yeatman,E.M.

English

Spiral - Imperial College Digital Repository

MODELLING FOR OPTIMISATION OF SELF-POWERED WIRELESS SENSOR NODESP. D. Mitcheson, D. C. Yates, E. M. Yeatman, T. C. Green, A. S. HolmesImperial College London, UKABSTRACTAchieving self-powered operation of an implantable sensoris difficult with current technology, despite the fact thatthe theoretical energy available for harvesting exceeds thetheoretical energy required. Moreover, the design andrealisation of such sensors nodes is a multi-domain task,requiring global system modelling and optimisation. Thispaper addresses how such systems can be modelled andoptimised by considering both the individual subsystems andtheir interdependence. The subsystems considered are: anenergy-harvesting generator, power converter and a radio link.Optimising these subsystems individually would result in alow overall system performance, but a global optimisationwould have too many parameters. In order to make theoptimisation and design practical it is suggested that thesystem is partitioned at the interface betwen the power supplyoutput and the load circuitry, allowing the optimisation tobe done in two parts whilst still finding a global optimum.Finally, we consider the dependence of power issues on devicesize, and show that effective performance from a body sensornode is achievable for a device volume in the cubic millimetresrange.Keywords: Micro-power generator, micropower supply,wireless sensor, ultra-low power radio1 INTRODUCTIONThe fields of ubiquitous computing and medical sensingrequire ultra-low power, miniaturised, autonomous devices,capable of wireless data transfer. They require a lifetime ofmany years meaning that batteries are insufficient as the solepower source [1]. Consequently these sensors must harvestenergy from their environment using a built-in generator,and additionally the power budget for the load electronics isvery limited. The power output from the energy-harvestinggenerator must be processed to a rail voltage suitable forthe load electronics or a secondary cell. Depending uponthe implementation of this generator, the power processingelectronics may have to convert, with high efficiency, verylow or very high voltages, through one or more orders ofmagnitude, to the rail voltage. The design of the powerprocessing electronics and the effectiveness of the mechanicalgenerator are closely linked and thus a combined optimisationis necessary.The power consumption of the load electronics is typicallydominated by the transceiver. The size constraint presentsa unique design challenge for the RF engineer, who mustconsider the trade-off between antenna efficiency and circuitlosses, both of which increase with frequency. Off-the-shelflow-power transceivers can only achieve data rates of tens ofbits per second [2] when operated at a sufficiently low dutycycle to be powered from an energy-harvesting generator. Suchlow data rates are insufficient for key applications such as ECGmeasurement.Various different transduction mechanisms are possible whenharvesting energy. This work only considers using kineticenergy as the energy source although many other forms arepossible [3, 4]. For electrostatic generators which harvestenergy from human body motion, the efficiency of the powerprocessing electronics reduces as the rail voltage drops,whereas the power consumption of the transmitter reduceswith reducing rail voltage. Consequently, once optimal powerelectronics and load electronics have been designed across thepossible variations in rail voltage, an optimal rail voltage canbe found in order to minimise the fraction of generated energyconsumed by the load. Any additional energy can be stored fortimes when the generator is inactive.2 POWER SUPPLYThe power supply comprises an energy-harvesting generator,power-processing electronics and associated controlelectronics. The operating principle of the generator isillustrated in Fig. 1, that is, when the frame experiencesacceleration (i.e. ÿ(t) 6= 0) the inertia of the proof mass causesthe mass to move relative to the frame and do work againsta damping force. The damping force is implemented usingpiezoelectric, electromagnetic or electrostatic forces and thusenergy dissipated in the damper of this model is the energythat can be converted into an electrical form.PSfrag replacementsmf (ż)ky(t)z(t)x(t)ZlFigure 1: Generalised mechanical modelling.2.1 Mechanical ModellingThe first considerations for maximising the power density ofthe generator are concerned with the basic configuration of thegenerator:1. How much of the generator volume should the massoccupy?2. What should the velocity-force characteristic of thedamping force be?3. Should the generator be resonant or non-resonant?It has been shown that setting the mass to occupy half thevolume [5] is optimal for sinusoidal acceleration inputs.Three generator architectures based around the second andthird questions were identified in [5] and their performancescompared across all operating conditions for the generator,as shown in Fig. 1. The three types are velocity-dampedresonant generator (VDRG), coulomb-damped resonantgenerator (CDRG) and coulomb-force parametric generator(CFPG). The optimal architecture is dependent upon operatingcondition, and as can be seen from the surface plot of Fig. 1, theCFPG is superior when the generator is small compared to theamplitude of the driving motion. This generator architecturewill be used to illustrate the next part of the modelling process.The CFPG is a non-linear, snap-action device [6], where themass only moves relative to the generator frame near the peakof the frame acceleration, in order to maximise the availableforce-distance product of the damper, and thus the energygenerated.2.2 Electro-mechanical ModellingWhilst choosing an architecture is technology independent(within the limits of what can be reasonably implemented),the next stage in design requires a decision on implementation.The CFPG requires a constant (Coulomb) force opposing therelative motion between the mass and frame. The easiest wayof achieving such forces in MEMS is with either a parallelplate capacitor operated under constant charge or a comb drivein constant voltage. A parallel plate in constant charge waschosen because higher forces can be achieved per unit volume.The capacitor is charged to low voltage at high capacitance.Energy is generated as the plates separate at constant charge,with the generated energy being captured when the capacitordischarges at minimum capacitance.In order for the generator to convert as much energy aspossible into an electrical form, it is important that thecharge placed on the capacitor at low voltage stays in placewhile the plates separate. Any leakage or charge sharingwith parasitic capacitances will reduce the effectiveness.Because the charging and discharging of the capacitor iscontrolled by semiconductor switches, and increasing the areaof these switches will increase their efficiency but decrease theeffectiveness of the generator, a combined electro-mechanicalsimulation is required. The most suitable platform for thissimulation work is the circuit simulator SPICE. In order tosimulate the generator in SPICE, a behavioural model ofthe mechanics and electrostatics was created. Part of this, aMEMS capacitor, is shown in Fig. 2.Results from an electro-mechanical simulation from SPICEare shown in Fig. 3. The top trace shows the behaviour ofthe mechanics, with the moving plate flying between thelimits of travel. The lower trace shows the voltages developedby the generator. This simulation does not include thepower processing electronics, although the simulation modelpresents its output on an electrical port in SPICE meaningthat combining the power electronics into the simulation isstraight-forward.Figure 2: SPICE behavioural model of MEMS capacitor.2.3 Device ModellingCustom semiconductor devices capable of switching highvoltages at high current density, whilst still presentingminimum parasitic capacitance to the generator, were designed0 0.5 1 1.5 2 2.5−2−1012Position [mm]Optimal Mass Trajectory0 0.5 1 1.5 2 2.50100020003000Time[s]Plate Voltage [V]Optimal Voltage ProfilePrecharge Mass strikes  bottom contactBreak−away Discharge Mass strikes top contact  Mass breaks−away    from bottom contact Generation Figure 3: SPICE simulation result.in a finite-element simulator [7]. Whilst this simulatorproduces accurate results for semiconductor performance, itis not possible to construct large circuit behavioural models(for example of the generator mechanics). Consequently, thecustom semiconductors have to be implemented in SPICE.Fig. 4 shows a SPICE subcircuit model used to simulate acustom designed power MOSFET. It should be noted that thesimple SPICE MOSFET model is not sufficiently accurateto describe this device because the standard model does notinclude JFET pinch at the drain end of the MOS channel.The device models can now be incorporated into the electro-mechanical system model in order to run full simulations ofthe power supply, and investigate optimal power electroniccircuit designs.PSfrag replacementsDGSRdri f t0 50 100 150 200 25001234x 10−3Vds [V]I d [A]FE ModelSPICE ModelFigure 4: SPICE subcircuit MOSFET model and curve traces.3 POWER USAGEThe loop antenna is well suited to wireless sensing applicationsbecause of its omnidirectional nature, its possible dual useas the inductor in an LC oscillator, and its widespread usein wireless power delivery. Previously a Colpitts oscillatortransmitter was reported in which a loop antenna doubledas the inductor in the LC tank [8]. In this work we havedeveloped a design methodology for minimising the powerconsumption of this type of oscillator transmitter given aconstraint on the maximum antenna size [2,9]. Optimisation ofthe design requires consideration of the desired characteristicsof an antenna in conjunction with those of the inductor in an LCoscillator and the frequency dependent losses of the RF MOStransistor.3.1 Antenna ModellingThe loop antenna has been simulated in MATLAB usinga combination of analytical and numerical techniques.Modelling the current distribution and input impedance ofthe electrically large loop antenna using the method detailedin [10] enables the variation of radiation resistance, directivity,radiation efficiency and Q-factor with the electrical size to beevaluated [2]. It has been shown that, given a certain maximalconstraint on the antenna size, the optimal transmissionfrequency in terms of maximum power transfer from thetransmitter antenna input to the receiver load corresponds to anantenna electrical size of approximately 0.2, as shown in fig 5.0 0.01 0.02 0.03 0.04 0.05 0.06 0.070.150.160.170.180.190.20.210.220.23Coil Radius [m]Optimal Circumference to Wavelength RatioFigure 5: Optimal electrical size of loop antenna.3.2 Device and Circuit ModellingRF circuits and devices are usually modelled using specialisedcircuit simulators such as Cadence’s SPECTRE RF (seetransient simulation example in Fig. 6). Such a simulator isunfortunately not suited to this optimisation, since the rangeand number of variables is simply too large. Each specificset of parameters requires a separate transient, periodicsteady-state and periodic noise analysis, which all needconsiderable computing time. Furthermore, these simulationsnormally need tweaking by the user to achieve meaningfulresults, making automation of such an optimisation processimpractical.PSfrag replacementsRLLM1M2DATAVDDC1C2VBiBFigure 6: Oscillator circuit and start up transient.The RF circuits and devices have thus also been modelled inMATLAB using a combination of analytical and numericaltechniques. The EKV model [11] has been used in conjunctionwith a high frequency model presented in [12] to model thetransistor (see Fig. 7). The required bias current for a particularoscillation voltage, given the antenna dimensions and operatingfrequency, has been evaluated using an energy conservationtechnique. The MATLAB simulations were compared withSPECTRE RF for specific circuit and device parameters toimprove the accuracy.PSfrag replacementsRGCGSCdsCgsrigmv′gsv′gsg′dsRDRSDGSFigure 7: High frequency MOSFET model.3.3 Combined OptimisationFigure 8 shows the preferred carrier frequency from thestandard ISM bands for a given maximum allowed antennasize. This has been found by combining the antenna,circuit and device analyses. The oscillation voltage neededfor successful data transfer has been calculated by simplemanipulation of the well known Friis transmission formulacombined with modelling of the oscillator linewidth using [13].0 0.01 0.02 0.03 0.04 0.05345678910Maximum Allowed Antenna Radius [m]Minimum Bias Current [µA]5.8GHz2.4GHz900MHz434MHzFigure 8: Minimum bias current for data transfer.4 GLOBAL OPTIMISATIONPreviously [5] we have shown that the generator outputdepends on the excitation amplitude Y0 and frequency ω,internal displacement Zl and proof mass m, according to:P ≈12Y0Zlω3m (1)This holds for the CFPG or for resonant devices operating atresonance. Let us now assume for the generator shape a flatsquare of dimensions a×a×αa where α << 1. This form willsupport an antenna coil of radius a/2. The optimal mass willoccupy approximately half the volume [14] leaving an internaldisplacement amplitude a/4. Then for a proof mass densityρ, substituting Y0ω2 for the maximum external acceleration A0,we have:P ≈116A0ωραa4 (2)A peak acceleration of about 1g (10m/s2) is typical of bodymotion [14] at about 1 Hz. Then, taking an aspect ratio, α = 0.1and ρ = 2×104 kg/m3 (gold), we obtainP ≈ 8×103a4 W/m4 (3)Note that (for α = 0.1) we can write this as:P ≈ 1.7V 4/3 mW/cm4 (4)where V is the generator volume.0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.610−210−1100101Device Size [cm]Power Consumption and Generation [µW]100% Duty Cycle10% Duty Cycle2.4GHz5.8GHz10kb/s1kb/s0.1kb/sFigure 9: Comparison of power generation with powerconsumption as a function of device size and data rate.Minimum power consumption as solid/dashed lines andmaximum power generation capability as dotted lines. Optimaltransmission frequency changes at a device size of 4 mm. Thereceiver noise figure is 20 dB and the radio link is assumed tooperate over a 1 m distance.The bias current results of Fig. 8 are easily converted toapproximate power consumption values for the transmitterby multiplying by VDD. Correct operation of the switchesM1 and M2 require VDD to be large enough to drive bothMOSFETS into saturation, so we choose VDD = 1V. Theaverage power consumption also scales with transmitterduty cycle (assuming negligible power during rest state).Meanwhile power generation scales with antenna radiusaccording to 3 and using r = a/2. We can also introduce aduty cycle for generation, corresponding to the fraction of timewhen external motion is available for generation. In Fig. 9 weplot transmitter power and generator output for several dutycycles of both transmitter and generator. The crossing pointsindicate the minimum size of the sensor node, assuming thegenerator dominates the size. It can be seen that, for example,with 10% generator duty cycle and an average transmissionrate of 0.1 kb/s, the minimum device dimension is 3 mm, sothat with the assumed aspect ratio α = 0.1 we have a generatorvolume of ≈ 10 mm3, or 0.01 cc, a size that is not excessivefor many body sensor applications. This device size is a lowerbound because a small amount of power will be required forcontrol and sensing electronics.5 CONCLUSIONSWe have described a number of issues associated withoptimisation of functional blocks in a self-powered bodysensor node, and shown a number of interactions betweenthese that require an integrated approach to design andoptimisation. By considering the dependence of bothtransmitter power consumption and generator output power ondevice dimensions, we have shown that effective performancefrom a body sensor node is achievable for a device volume of10 cubic millimetres.References[1] E. M. Yeatman, “Advances in Power Sources for WirelessSensor Nodes,” in International Workshop on Wearableand Implantable Body Sensor Networks Proceedings,Imperial College London, U.K., April 2004.[2] D. C. Yates, A. S. Holmes, and A. J. Burdett, “Optimaltransmission frequency for ultralow-power short-rangeradio links,” IEEE Transactions on Circuits and SystemsPart 1, vol. 51, no. 7, pp. 1405–1413, July 2004.[3] S. Roundy, P. K. Wright, and J. M. Rabaey, EnergyScavenging for Wireless Sensor Networks, 1st ed.Boston, Massachusetts: Kluwer Academic Publishers,2003.[4] T. Starner and J. A. Paradiso, “Human Generated Powerfor Mobile Electronics,” in Low Power ElectronicsDesign, C. Piquet, Ed. CRC Press, 2004, to be published.[5] P. D. Mitcheson, T. C. Green, E. M. Yeatman,and A. S. Holmes, “Architectures for Vibration-Driven Micropower Generators,” IEEE/ASME Journal ofMicroelectromechanical Systems, vol. 13, no. 3, pp. 429–440, June 2004.[6] P. D. Mitcheson, P. Miao, B. H. Stark, E. M. Yeatman,A. S. Holmes, and T. C. Green, “MEMS ElectrostaticMicro-Power Generator for Low Frequency Operation,”Sensors and Actuators, part A, vol. 115, no. 2–3, pp. 523–529, 2004.[7] B. H. Stark, P. D. Mitcheson, P. Miao, T. C. Green,E. M. Yeatman, and A. S. Holmes, “Power processingissues in electrostatic micro-power generators,” in 35thIEEE Annual Power Electronics Spoecialists Conference,Aachen, Germany, 2004, pp. 4156–4162.[8] B. Ziaie, K. Najafi, and D. J. Anderson, “A low-powerminiature transmitter using a low-loss silicon platformfor biotelemetry,” in Proc. 19th IEEE Internationalconference of Engineering in Medicine and BiologySociety, vol. 5, 1997, pp. 2221–2224.[9] D. C. Yates and A. S. Holmes, “Loop antenna designfor ultra low power transmitters,” in IEEE InternationalWorkshop on Antenna Technology, Singapore, 2005,accepted.[10] R. W. P. King and G. S. Smith, Antennas in matter:Fundamentals, theory and applications. Cambridge,MA: MIT Press, 1981.[11] C. C. Enz, F. Krummenacher, and E. A. Vittoz, “Ananalytical MOS transistor model valid in all regions ofoperation and dedicated to low-voltage and low-currentapplications,” Analog Integrated Circuits and SignalProcessing, pp. 83–114, July 1995.[12] T. Manku, “Microwave CMOS - device physics anddesign,” IEEE Journal of Solid State Circuits, vol. 34,no. 3, pp. 227–285, March 1999.[13] D. Ham and A. Hajimiri, “Virtual damping and Einsteinrelation in oscillators,” IEEE Journal of Solid StateCircuits, vol. 38, no. 3, pp. 407–418, March 2003.[14] T. von Büren, P. D. Mitcheson, T. C. Green, E. M.Yeatman, A. S. Holmes, and G. Tröster, “Optimizationof Inertial Micropower Generators for Human WalkingMotion,” IEEE Sensors Journal, 2005, in press.

Modelling for optimisation of self-powered wireless sensor nodes

Achieving self-powered operation of an implantable sensor is difcult with current technology, despite the fact that the theoretical energy available for harvesting exceeds the theoretical energy required. Moreover, the design and realisation of such sensors nodes is a multi-domain task, requiring global system modelling and optimisation. This paper addresses how such systems can be modelled and optimised by considering both the individual subsystems and their interdependence. The subsystems considered are: an energy-harvesting generator, power converter and a radio link. Optimising these subsystems individually would result in a low overall system performance, but a global optimisation would have too many parameters. In order to make the optimisation and design practical it is suggested that the system is partitioned at the interface betwen the power supply output and the load circuitry, allowing the optimisation to be done in two parts whilst still nding a global optimum. Finally, we consider the dependence of power issues on device size, and show that effective performance from a body sensor node is achievable for a device volume in the cubic millimetres range

Modelling for optimisation of self-powered wireless sensor nodes

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