Hardware Implementation of Maximum Power Point Tracking for Thermoelectric Generators

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  • Hardware Implementation of Maximum Power Point Trackingfor Thermoelectric Generators

    OTHMAN MAGANGA,1,4,5 NAVNEESH PHILLIP,1 KEITH J. BURNHAM,1

    ANDREA MONTECUCCO,2 JONATHAN SIVITER,2 ANDREW KNOX,2

    and KEVIN SIMPSON3

    1.Control Theory and Applications Centre, Faculty of Engineering and Computing, CoventryUniversity, Priory Street, Coventry CV1 5FB, UK. 2.Energy Group, School of Engineering,University of Glasgow, Glasgow, UK. 3.European Thermodynamics Ltd., Leicester, UK.4.e-mail: aa9793@coventry.ac.uk. 5.e-mail: othman.maganga@coventry.ac.uk

    This work describes the practical implementation of two maximum powerpoint tracking (MPPT) algorithms, namely those of perturb and observe, andextremum seeking control. The proprietary dSPACE system is used to performhardware in the loop (HIL) simulation whereby the two control algorithms areimplemented using the MATLAB/Simulink (Mathworks, Natick, MA) soft-ware environment in order to control a synchronous buckboost converterconnected to two commercial thermoelectric modules. The process of per-forming HIL simulation using dSPACE is discussed, and a comparisonbetween experimental and simulated results is highlighted. The experimentalresults demonstrate the validity of the two MPPT algorithms, and in conclu-sion the benefits and limitations of real-time implementation of MPPT con-trollers using dSPACE are discussed.

    Key words: MPPT, TEG, thermoelectric, dSPACE, P&O, ESC

    AbbreviationsTEG Thermoelectric generatorMPP Maximum power pointMPPT Maximum power point trackingP&O Perturb and observeESC Extremum seeking control

    INTRODUCTION

    In the last decade, investigation into thermoelec-tric generators (TEGs) for waste heat recovery inautomotive applications has seen several advance-ments and the operational understanding of TEGsas a system has significantly improved. This isattributed to initial developments of models forestimation of fuel economy benefits,1,2 morein-depth modeling and design of heat exchangers35

    and thermoelectric module subsystems,6,7 as well as

    research into material selection.7,8 Despite theseadvances the science of TEGs still remains open toresearch in many areas; For example, one area isoptimization of the electrical interface between theTEG system and the load, which in automotiveapplications is most often the 12-V battery. Thiselectrical interface or power conditioning unit(PCU) includes a direct current (DC)DC convertercontrolled by a maximum power point tracking(MPPT) algorithm to maximize power transfer fromthe TEG to the load.

    MPPT is a method to obtain the optimum powergenerating point for a given system and load. Theneed for MPPT algorithms exists mainly for vari-able output systems such as TEGs and photovoltaics(PVs) where output power reduction due to loadmismatch is evident. As an example, for TEGs thispower reduction is caused by the variable temper-ature across the devices during normal operation.MPPT enables efficient interfacing of TEG and/orPV systems with a DCDC converter to transfermaximum power at a fixed voltage. Most MPPTalgorithms implemented on TEGs have been adoptedfrom PV systems where the use of MPPT is well(Received July 1, 2013; accepted January 18, 2014)

    Journal of ELECTRONIC MATERIALS

    DOI: 10.1007/s11664-014-3046-0 2014 TMS

  • established. Of these, some common methods usedfor TEGs are perturb and observe (P&O),913 incre-mental conductance (IC),14,15 and fractional open-circuit-voltage/short-circuit-current (Voc/Isc),

    16,17

    which is known as the constant voltage (CV)/con-stant current control method. Given that the steady-state voltagecurrent (VI) characteristic of TEGs islinear6,18,19 and that the power curve is parabolic,the fractional Voc method does not require currentsensing, and it is the least computationally intensivebecause the duty cycle for the converter is deter-mined by taking half of Voc. This, however, requiresintermittent disconnection of the TEG from the loadto establish the prevailing Voc value and can lead toundesired transients and reduced efficiency foroperation in dynamic thermal environments. Con-versely, P&O and IC are known as hill climbingmethods which compare current with previous VIvalues to determine the increase or decrease of theperturbation gain. P&O uses VI values to calculatepower or uses V or I for comparison, whereas ICtakes the derivative of VI values to determine thegradient of the power curve under the principle thatthe gradient at maximum power is zero. Whilst bothmethods are commonly used in PV systems due totheir ease of implementation, IC is able to identify ifthe maximum power point (MPP) is reached or notbut is computationally intensive and as a conse-quence converges more slowly to the MPP.20 TrueMPP cannot be achieved using P&O due to contin-uous perturbation which causes the operating pointto oscillate around the MPP.

    One disadvantage of the P&O and IC methods isthat for accurate tracking of the MPP the pertur-bation gain is required to be small to minimize therange of the limit cycle, which in turn degrades thealgorithms transient tracking ability. To addressthe deficiencies found for the above-mentionedmethods, the requirement is for an algorithm whichcan work without disconnecting the TEG and loadand perform optimally in transient and steady-stateoperation. One such algorithm is extremum seekingcontrol (ESC), which has shown performance supe-rior to other well-known MPPT algorithms such asP&O for PV systems.21 The perceived advantage isattributed to the ability of ESC to converge morerapidly whilst retaining steady-state performancesimilar to the P&O method. Phillip et al.22 havepreviously shown via simulation that, similar toperformance with PV systems, ESC for TEGs doesindeed perform as expected when compared withP&O. This paper extends the above work andexperimentally validates the results found fromsimulation.

    ESC operates in a closed-loop fashion as shown inFig. 1, where a perturbation signal with an initialduty cycle is fed to the unknown system. Theresulting output from the system is high-pass fil-tered to remove any DC offset and then comparedwith the original perturbation signal to obtain thenew duty cycle. This is iteratively repeated until the

    optimal power point is found, at which point thealgorithm enters a limit cycle as with P&O asillustrated in Fig. 2. Pmax denotes maximum power,and d* denotes duty cycle at maximum power.Whilst this method has been shown to work well,the main drawback with ESC is the large number ofparameters that require tuning for optimal opera-tion. ESC parameters are: perturbation gain B,integrator gain K, perturbation frequency w, andhigh-pass filter frequency wh. The overall perfor-mance of ESC is dependent on these parameters;For example, convergence is mainly dependent on Band K. Faster convergence can be achieved whenlarge values are selected, however this introducesoscillations and noise sensitivity to disturbances.23

    In comparison, P&O is simple and requires min-imal effort for implementation. A detailed explana-tion of ESC and P&O can be found in Ref. 22.

    Thus far, much research on MPPT for TEGapplications has been focused on validating onecontroller at a time as well as comparison of PCUtopologies with implementation of MPPT, investi-gating power output efficiency for different DCDCconverter types, TEG module configurations, andmodule- versus stack-level MPPT implementa-tion.2426 The work presented in this paper does notfocus on the effect of MPPT at system level; rather,it uses a simple PCU topology to compare two dif-ferent MPPT algorithms on the same TEG system.To the authors knowledge, this paper presents thefirst experimental results for the application of ESCto TEGs.

    EXPERIMENTAL PROCEDURES

    As explained in the Introduction, the techniqueused to maximize the electrical power transferredfrom the TEG to the external circuit is implementedby interfacing the TEG to a battery load through aDCDC converter controlled by a MPPT algorithm.This section describes the instrumentation anddevices used to gather the experimental resultsobtained with physical TEGs and with an emulationof the behavior of the TEGs. The steady-state elec-

    Fig. 1. Schematic diagram of the extremum seeking controller.

    Maganga, Phillip, Burnham, Montecucco, Siviter, Knox, and Simpson

  • trical characteristic of a TEG can be represented by avoltage source in series with a resistor; therefore thesteady-state behavior can be emulated using a powersupply unit (PSU) connected in series with a resistoror an electronic load in constant-resistance mode.Figure 3 illustrates a schematic of the experimentalapparatus.

    The TEGs are connected to a synchronous buckboost DCDC electronic converter, whose output isconnected to a PSU in parallel with an electronicload in CV mode. The former guarantees a constantoutput voltage while the latter sinks the currentprovided by the DCDC converter, thus emulatingthe behavior of a battery. The real-time prototypingunit MicroAutoBox (dSPACE GmbH, Germany) isused to interface the electronic converter to a per-sonal computer (PC): the input and output voltages(VIN and VOUT) and currents (IIN and IOUT) aremeasured by the converter, while the MicroAutoBoxsends the pulse width modulation (PWM) signals,180 antiphase, that control the switching operationof the DCDC converter. The PC runs the MPPTalgorithms in the mathematical software MATLAB/Simulink.

    TEG TEST RIG AND ELECTRICALCHARACTERIZATION

    The measurement test rig described at theInternational Conference of Thermoelectrics 2012(ICT12)27 has been used for numerous experimen-tal tests with real TEG modules. Figure 4 shows thearchitecture of the system, which is contained in astandard 19-inch equipment rack and constitutes astandalone system able to simultaneously test up tofour TEG modules independently of one another.Figure 4 shows one of four identical channels. Adata logger unit is used to record numerous tem-perature and mechanical pressure measurementsfrom the test fixture. Heater power is provided by aset of four DC power supplies; a chiller unit is usedto maintain a constant temperature on the cold sideof the system, and an electronic load is available toabsorb power from each TEG under test if required.All the instruments are fully programmable andoperated from a laptop PC running an Agilent VEEPro program (Agilent Technologies, Santa Clara,CA).

    Two commercial 40 mm 9 40 mm TEG modulesby European Thermodynamics Ltd. (GM250-127-14-10) were used in the experimental tests. Both weretested separately to obtain their individual electri-cal characteristics at a constant mechanical load inthe test fixture of 1920 N (1.2 MPa), for three dif-ferent temperature gradients: 100C, 150C, and200C. The cold block water supply was maintainedat 20C for all the tests presented in this paper. Theresulting VI and PI curves for TEG #2 are pre-sented in Fig. 5, while Table I lists the importantelectrical parameters for both TEG modules.

    The last column of Table I (Variance) showsthat the performance variance between the poweroutput of the modules tested is less than 1%. Thisslight difference may be due to a small thermalimpedance mismatch in the experimental apparatusor due to TEG manufacturing tolerances. A conse-quence of this difference is that when connected inseries their combined output power will be slightlyless than the sum of the individual powers. It must

    Fig. 2. Limit cycle characteristics for perturb and observe and ESC.

    Fig. 3. Schematic diagram of the connections between the instru-ments and devices used for the experimental tests.

    Fig. 4. Schematic representing the architecture of the measurementtest rig for thermoelectric devices.

    Hardware Implementation of Maximum Power Point Tracking for Thermoelectric Generators

  • also be noted that the real MPP might be betweentwo measured load values; however, the differencein power produced will always be less than 0.5%.Considering these factors and the variance datain Table I, it can be concluded that the perfor-mance values provided in Table I have a worst-caseaccuracy of 1%.

    Using the mathematical fitting technique describedby Montecucco et al.,27 it is possible to determine theoutput voltage and power from the TEGs as a functionof their load current, for any imposed temperaturegradient. Example results are provided in Table II fortemperature gradients between 25C and 225C in25C increments. The rightmost pair of columns inTable II show that the error between the experimen-tal value and the mathematically determined valuedoes not exceed 5%. The error depends on the factthat, due to material properties, the open-circuitvoltage has a nonlinear relationship with low andhigh temperature gradients; the open-circuit voltage

    reaches an asymptote at a certain high temperaturedifference.

    DCDC CONVERTER

    The circuit schematic of the synchronous buckboost converter used in this work is sketched inFig. 6. The Schottky power diode D4 replaces thecommonly used fourth metaloxidesemiconductorfield-effect transistor (MOSFET)25 to block reversecurrent flow and prevent the battery connected atthe output from discharging through the converterduring discontinuous conduction mode. PWM1 andPWM2 are 180 out of phase with sufficient dead-time to prevent cross-conduction of M1 and M2. Thebasic functioning of the converter is as follows: Theinductor L is charged when PWM1 is active high(M1 and M3 closed), and it then discharges to theload when PWM2 closes M2 (M1 and M3 open).Current passes through D4 and the body diode of

    Fig. 5. Electrical characterization for TEG #2 at constant mechanical pressure of 190 kg (1.2 MPa) and for three different temperature gradients:100C, 150C, and 200C between the hot and cold sides of the thermoelectric module.

    Table I. Major experimental electrical characteristics of the two TEG modules for three differenttemperature gradients: 100C, 150C, and 200C

    Temp. Diff. TEG #1 TEG #2 Variance

    DT (C) Rint (X) Voc (V) Pmax (W) Rint (X) Voc (V) Pmax (W) |Pmax1 2 Pmax2| (%)

    100 1.81 4.52 2.82 1.79 4.51 2.83 0.6150 2.01 6.91 5.91 1.97 6.86 5.92 0.2200 2.16 8.83 8.97 2.14 8.83 9.04 0.8

    Maganga, Phillip, Burnham, Montecucco, Siviter, Knox, and Simpson

  • M2 during the dead-time between the antiphasePWM pulses. The converter can also work in boostmode when M1 is left closed and M2 left open, or inbuck mode if M3 is kept open.

    Input and output currents are sensed through thedifferential amplification of the voltage across high-precision/power sense resistors placed in series withthe converters input and output terminals. Thenominal input power of the converter is 35 W at17.5 V, 2 A. Its electrical efficiency at 34 W inputpower (11.35 V, 3 A) is 88.2%. The convertersprinted circuit board (PCB) is shown in Fig. 7.

    DSPACE INTERFACE

    The MicroAutoBox is a portable dSPACE hard-ware used for real-time application to perform var-ious rapid control prototyping. It comprises multiplein-built PWM channels, of which two are used todrive the MOSFET gate drivers of the synchronousbuckboost DCDC c...

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