The market of electronic systems such as Electric Vehicles, Smart Grids, Robotics and Renewable Energy Systems is rapidly growing. The increasing demand of electrical systems has led consequently to a deeper study of the batteries and their management. It became necessary to use the Battery Management System (BMS) to allow the batteries to work properly, monitoring and controlling the variables that modify the behaviour of the pack. The unbalancing of the batteries is one of the main aspects that has to be taken into account in the design of the BMS because it leads to problems of over-charging and over-discharging that cause shorter autonomy of the electrical system and faster degradation of the batteries. In order to equalize the states of charge of the pack’s cells several balancing systems have been proposed, basing their equalization process on the use of different electric components such as resistors, inductors, capacitors and transformers. The core of this thesis is the battery modelling, the development of a new balancing control system based on the reconfiguration topologies and the optimization of the reconfiguration strategy through Greedy Optimization methods and Dynamic Programming. First of all the batteries have been studied, modelled in Matlab/Simulink and parametrized as electrical systems through CDT/HPPC tests. The standard balancing methods and the reconfiguration topologies have been analysed in order to define advantages and disadvantages leading to the definition of a new topology able to benefit of the self-balancing property of the batteries. The pack model has been built in Matlab/Simulink and then the optimization strategies have been adopted in order to get the best balancing properties, analysed through performance indices (PI). The system has been tested through the Urban Dynamometer Driving Schedule (UDDS) and the New European Driving Cycle (NEDC) and then compared with the standard Bidirectional DC/DC Balancing method.
Il mercato di sistemi elettronici come Veicoli Elettrici, Smartgrid, Robotica e Sistemi a Energia Rinnovabile è in rapida crescita. Il rapido aumento della domanda di sistemi elettrici ha portato di conseguenza a uno studio più approfondito delle batterie e della loro gestione. È diventato necessario utilizzare sistemi di gestione delle batterie (BMS) per consentire il corretto funzionamento, monitorando e controllando le variabili che modificano il comportamento del pacco batteria. Lo sbilanciamento di carica delle batterie è uno degli aspetti principali che deve essere preso in considerazione nella progettazione del BMS perché porta a problemi di sovraccarica e di scarica eccessiva che causano una minore autonomia del sistema elettrico e un degrado più rapido del batterie. Al fine di equalizzare gli stati di carica delle celle del pacco batteria sono stati proposti diversi sistemi di bilanciamento che basano il loro processo di equalizzazione sull’uso di diversi componenti elettrici come resistori, induttori, condensatori e trasformatori. Il nucleo della tesi è la modellizzazione delle batterie, lo sviluppo di un nuovo sistema di controllo del bilanciamento basato sulle topologie di riconfigurazione e l’ottimizzazione della strategia di riconfigurazione attraverso Greedy Optimization e Dynamic Programming. Le batterie sono state analizzate, modellate in Matlab/ Simulink e parametrizzate come sistemi elettrici attraverso CDT/HPPC test. I metodi di bilanciamento standard e le topologie di riconfigurazione sono stati analizzati al fine di definire vantaggi e svantaggi per determinare una nuova topologia in grado di beneficiare della proprietà di auto-bilanciamento delle batterie. Il modello del sistema è stato creato in Matlab/Simulink e sono state adottate le strategie di ottimizzazione per massimizzare il bilanciamento, analizzato attraverso gli indici di prestazione (PI). Il sistema è stato testato attraverso Urban Dynamometer Driving Schedule (UDDS) e New European Driving Cycle (NEDC) e confrontato con il metodo di bilanciamento standard DC/DC bidirezionale.
Li(NiCoMn)02 battery modelling and parametrization through CDT/HPPC test and optimization of reconfigurable battery pack balancing (RBPB)
Violino, Giovanni
2019/2020
Abstract
The market of electronic systems such as Electric Vehicles, Smart Grids, Robotics and Renewable Energy Systems is rapidly growing. The increasing demand of electrical systems has led consequently to a deeper study of the batteries and their management. It became necessary to use the Battery Management System (BMS) to allow the batteries to work properly, monitoring and controlling the variables that modify the behaviour of the pack. The unbalancing of the batteries is one of the main aspects that has to be taken into account in the design of the BMS because it leads to problems of over-charging and over-discharging that cause shorter autonomy of the electrical system and faster degradation of the batteries. In order to equalize the states of charge of the pack’s cells several balancing systems have been proposed, basing their equalization process on the use of different electric components such as resistors, inductors, capacitors and transformers. The core of this thesis is the battery modelling, the development of a new balancing control system based on the reconfiguration topologies and the optimization of the reconfiguration strategy through Greedy Optimization methods and Dynamic Programming. First of all the batteries have been studied, modelled in Matlab/Simulink and parametrized as electrical systems through CDT/HPPC tests. The standard balancing methods and the reconfiguration topologies have been analysed in order to define advantages and disadvantages leading to the definition of a new topology able to benefit of the self-balancing property of the batteries. The pack model has been built in Matlab/Simulink and then the optimization strategies have been adopted in order to get the best balancing properties, analysed through performance indices (PI). The system has been tested through the Urban Dynamometer Driving Schedule (UDDS) and the New European Driving Cycle (NEDC) and then compared with the standard Bidirectional DC/DC Balancing method.| File | Dimensione | Formato | |
|---|---|---|---|
|
2020_07_Violino.pdf
non accessibile
Descrizione: testo della tesi
Dimensione
4.15 MB
Formato
Adobe PDF
|
4.15 MB | Adobe PDF | Visualizza/Apri |
I documenti in POLITesi sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/10589/165488