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Elenco Pubblicazioni - Publications (1433)

M. Piotto, S. Del Cesta, G. Argnenio, R. Simmarano, P. Bruschi, "A Compact Low-Offset Instrumentation Amplifier with Wide Input and Output Ranges", Congresso Nazionale Sensori (CNS), 2016

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In this work, a new architecture for the design of very compact instrumentation amplifiers is proposed. The amplifier has been specifically developed for use as a versatile block for sensor interfacing. The most innovative feature…
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PIETRO NANNIPIERI, [...], ROBERTO DI RIENZO, LUCA FANUCCI, FEDERICO BARONTI:"THE U-PHOS EXPERIENCE WITHIN THE ESA STUDENT REXUS/BEXUS PROGRAMME: A REAL SPACE HANDS-ON OPPORTUNITY", 2017 IEEE EDUCON

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U-PHOS (Upgraded PHP Only for Space) is a project developed by a team of students from the University of Pisa with the goal to analyze and characterize the behavior of a Pulsating Heat Pipe (PHP),…
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M. Piotto, F. Dell'Agnello, S. Del Cesta, M. Bruschi, "Integrated Thermal Flow Sensors with Programmable Power-Sensitivity Trade-Off" Cogresso Nazionale Sensori (CNS), 2016

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A thermal flow sensor integrated with a programmable electronic interface into the same chip is proposed. The sensing structure is a micro-calorimeter with a double heater configuration fabricated with a simple post-processing technique applied to…
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R. MORELLO, R. DI RIENZO, F. BARONTI, R. RONCELLA AND R. SALETTI, "SYSTEM ON CHIP BATTERY STATE ESTIMATOR: E-BIKE CASE STUDY", IECON 2016 - 42ND ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, FLORENCE, 2016

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This paper discusses the hardware implementation and experimental validation of a model-based battery state estimator. The model parameters are identified online using the moving window least squares method. The estimator is implemented in a field…
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R. MORELLO, R. DI RIENZO, R. RONCELLA, R. SALETTI AND F. BARONTI, "TUNING OF MOVING WINDOW LEAST SQUARES-BASED ALGORITHM FOR ONLINE BATTERY PARAMETER ESTIMATION," SMACD 2017, GIARDINI NAXOS, ITALY, 2017, PP. 1-4.

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Online battery parameter identification algorithms, such as the Moving Window Least Squares, allow model-based state estimators with low computational intensity to be very accurate. This paper presents a procedure for tuning the algorithm parameters by…
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