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7/03 – “Hybrid electric vehicles”: ne parla Simona Onori della Stanford University

Giovedì 7 marzo, in aula B5  – Edificio Nuova Didattica della macroarea di Ingegneria, alle h. 16, la professoressa Simona Onori della Stanford University terrà un seminario dal titolo “Hybrid electric vehicles: energy management strategies and tools for optimal energy storage systems selection”. La prof. Onori, tra l’altro, ha conseguito il dottorato di ricerca in Computer Science and Control presso Ingegneria “Tor Vergata”.

Gli organizzatori dell’incontro, tra cui il prof Vincenzo Mulone, oltre a coinvolgere gli studenti di “Sistemi E Componenti Per La Conversione Dell’energia Da Fonti Rinnovabili” del corso di laurea in Ingegneria Energetica  invitano vivamente tutti gli interessati a partecipare.

 

abstract

 

Hybrid vehicles offer additional degrees of freedom in controlling the instantaneous torque delivered to the wheels due to their more complex powertrain architecture. This ‘content-rich’ architecture provides many opportunities to improve fuel economy and reduce emissions. Realistic figures of achieavable improvement in fuel economy in HEVs range from 10% for mild hybrids to more 30% for highly hybridized vehicles. This potential can be realized only with a sophisticated control system that optimizes energy flow within the vehicle. Adopting systematic model-optimization methods, using meaningful objective functions and optimal control tools to improve the energy management controller give a more formal framework to deal with such a problem.

In this talk, we will present developments and trends of control and optimization for supervisory controllers in hybrid electric vehicles using optimization tools and we also present solutions for the selection and sizing of energy storage technologies (either in a standalone or hybrid configuration).

 

 

 

1/03 – Conferenza Prof. John M. Cioffi (Stanford University) al Deloitte Auditorium

Il primo marzo alle ore 15 presso l’Audutorium Deloitte a Roma il prof. John M. Cioffi professore emerito alla Stanford University terrà una conferenza dal titolo AI in planning the ubiquitous 1 GBPS Access Network.

Consulta QUI l’agenda dell’evento

Abstract

Access networks evolution to ubiquitous 1 Gbps can profit from the use of data sciences, both analytics and optimization. A range of both fixed and wireless access-connectivity options exist and no single choice is most efficient. Thus, the continuous artificially intelligent use of network data can augment planning exercises to make economical choices for access network evolution. This talk will review some of these methods and suggest possible gains and strategies that might be pursued to accelerate efficiently progress towards the ubiquitous 1 Gbps goal.

 

BIO

John M. Cioffi taught Stanford’s graduate electrical engineering course sequence in digital communications for over 20 years from 1986 to 2008, when he retired to emeritus. Cioffi’s research interests were in the theory of transmitting the highest possible data rates on a number of different communications channels, many of which efforts were spun out of Stanford through he and/or his many former PhD students to companies, most notably including the basic designed used worldwide on more than 500 million DSL connections. Cioffi also over saw the prototype developments for the worlds first cable modem and digital-audio broadcast system. Cioffi pioneering the use of remote management algorithms to improve (over the internet or cloud) both wireline (DSL) and wireless (Wi-Fi) physical-layer transmission performance, an area often known as Dynamic Spectrum Management or Dynamic Line Management. Cioffi was co-inventer on basic patents for vectored DSL transmission and optimized MIMO wireless transmission. In his early career, Cioffi developed the worlds first full-duplex voiceband data modem while at Bell Laboratories, and the worlds first adaptively equalized disk read channel while at IBM. His courses and research projects over the years centered on these areas.

Per l’accredito, inviare una mail cmorleo@deloitte.it