This work presents a hardware/software data acquisition system created for monitoring the temperature in real time of the cells in Air-Cooled Polymer Electrolyte Fuel Cells (AC-PEFC). data exchange (DAQ) program can perform nonintrusive temperatures measurements of each specific cell of an AC-PEFC bunch of any power (from w to kilowatts). The bunch power is certainly related to the temperatures gradient; i.age., a higher power corresponds to a higher bunch surface area, and higher temperatures difference between the coldest and the hottest stage consequently. The designed DAQ system has been implemented with the low-cost open-source platform Arduino, and it is usually completed with a modular virtual instrument that has been designed using NI LabVIEW. Heat vs time development of all the cells of an AC-PEFC both together and individually can be registered and supervised. The paper explains comprehensively the developed DAQ system together with experimental results that demonstrate the suitability of the system. row up to row), leaving eight cells (the stack used it SIRT3 this work has 80 cells) between each pair of sensing rows (Physique 4). Of course, this distribution can be adapted to any other structural stack design. Because of the design, we must process 30 analog signals. To do this with a single conditioning signal, we have made the decision to multiplex these signals. The thermal inertia [40] at the measurement points is usually much slower than the purchase time of a multiplexer; therefore, it is usually not necessary to acquire the 30 heat measurements at exactly the same time. Following this reasoning, we have used two 16-channels analog multiplexers to multiplex the 30 heat measurement signals. All the multiplexed signals go to the same conditioning signal built with a general-purpose operational amplifier (Op. Amp., observe Physique 5). This can be a good answer, since as the sensors are the same; the electric adjustable to end up being prepared is certainly the same also, as well as its range of beliefs. Body 5 DAQ program structures. Regarding to producer data [41], the optimum heat range alternative is certainly provided by a cell located in the middle of the bunch (the most popular stage, cell #40) and these positioned on the higher (cell #80) and on the lower boundary (cell #1). This difference between the most popular and coldest factors can rise up to 8 C, therefore this corresponds to a optimum heat range alternative of 0.2 C/cell. In our case, as we possess mentioned above, there are 10 realizing rows distributed along the entire bunch and this corresponds to departing eight free of charge cells between each realizing line. This will correspond to a optimum alternative of 8 cells 0.2 C/cell = 1.6 C. After that, the developed DAQ program for cell temperature monitoring shall give us more than CS-088 enough temperature information approximately the cell temperature distribution. Additionally, distributing the receptors rows along the bunch missing the same quantity of cells between each consecutive sensing row, will give a actual idea about the whole heat distribution. If the user would like to have measurements in all the cells of the collection under study, 80 3 = 240 NTC detectors would become needed and CS-088 consequently 240/16 = 15 analog multiplexers. However the goal of the paper and the developed prototype is definitely to demonstrate the feasibility of the proposal, for which we have limited the quantity of analog inputs to 32 (two multiplexers of 16 inputs each one), with which we can cover 10 cells with three measurements each one (30 NTCs). However, the scalability of the design allows the quantity of inputs to become as many as the user desires. For example, by keeping the same plan as in Number 5 and placing an additional CS-088 multiplexer governed by Arduino, we could increase the quantity of DAQ inputs to 48 (16 3), and so on. The training signal adapts the amplitude of the signal to the Arduino input. The Arduino microcontroller is definitely responsible for governing the opening of multiplexer inputs, electrical supply to all electronics, convert the analog temp signals into digital terms and communicate the hardware with the modular Virtual Instrument (VI) (please observe Appendix A for the Arduino screenplay). From the Arduino, all the temp data are transmitted in digital file format (by a USB slot) to the modular VI. To make simpler the DAQ system and make it very flexible and portable, its same USB port serves as the Arduino power supply and from it to the rest of the electronics. Table 1 summarizes the main characteristics of the products used in the developed DAQ.