Michele Vitelli

• University of Cassino and Southern Lazio

Lithium-ion (Li-ion) batteries are crucial in numerous applications, including portable electronics, electric vehicles, and energy storage systems. Electrochemical Impedance Spectroscopy (EIS) is a powerful technique for characterizing batteries, providing valuable insights into charge transfer kinetics like ion diffusion and interfacial reactions....

This paper presents a one data wire communication protocol, developed by Sensichips s.r.l., for multi-sensor readout applications with advantages in transfer efficiency and readout speed over currently used protocols. The protocol has been named Sensibus, it is a multi-drop single master multiple slaves type asynchronous protocol, and takes some fe...

The paper proposes a new experimental measurement method for State of Charge (SoC) estimation able to optimize between measurement time and target Accuracy adoptable in Battery Management System (BMS) design where both these parameters are key parameters for the overall management performance. The method is applicable when the SoC is estimated in c...

In this paper, a feasibility study of a shuntless coulomb counting method for estimating the state of charge (SOC) of a battery is presented. Contrary to conventional coulomb counting, the proposed method does not require an external resistive shunt; it instead only requires voltage measurements performed on the battery under test while it is opera...

A compact electronic circuit capable of performing Electrochemical Impedance Spectroscopy (EIS) on either single Lithium-ion cells or modules formed by the series of two cells is presented. The proposed device, named Double Cell Management Unit (DCMU), constitutes an important improvement to a recently proposed cell management unit, which combined...

This paper presents selected interim results of the H2020 project 3beLiEVe, which aims to deliver next-generation Lithium-Nickel-Manganese-Oxide (Generation 3b) battery cells for automotive applications, encompassing research activities across three pillars: (i) Selection and optimisation of the cathode (LNMO) and anode (Si/C) materials, as well as...

The technological step towards sensors’ miniaturization, low-cost platforms, and evolved communication paradigms is rapidly moving the monitoring and computation tasks to the edge, causing the joint use of the Internet of Things (IoT) and machine learning (ML) to be massively employed. Edge devices are often composed of sensors and actuators, and t...

The problem of detecting illegal pollutants in wastewater is of fundamental importance for public health and security. The availability of distributed, low–cost and low–power monitoring systems, particularly enforced by IoT communication mechanisms and low-complexity machine learning algorithms, would make it feasible and easy to manage in a widesp...

The detection of contaminants in several environments (e.g., air, water, sewage systems) is of paramount importance to protect people and predict possible dangerous circumstances. Most works do this using classical Machine Learning tools that act on the acquired measurement data. This paper introduces two main elements: a low-cost platform to acqui...

Water monitoring systems continuously working ensure real–time pollutant detection capabilities according to their sensitivity and specificity. It is necessary to balance such features because, although being able to sense several substances is a desired feature, the reduction of false positives is a primary goal a classification system should have...

To better asses the ageing and to reduce the hazards involved in the use of Lithium-Ion Batteries, multi-measurand monitoring units and strategies are urged. In this paper, a Cell Management Unit, based on the SENSIPLUS chip, a recently introduced multichannel, multi-mode sensor interface, is described. SENSIPLUS is a single System on a Chip combin...