The present Master thesis is dedicated to the study and development of optimized smart-charging algorithms for hybrid and electric vehicles. After having described the hardware architecture and infrastructures involved in such a feature, smart-charging protocols will be detailed to set up the context of this work. Then, the inherent complexity of the problem will be stated as a constrained optimization problem and solutions to solve it will be investigated. A systematic method to build optimal solutions will be presented for the “Off-Peak” application. Additionally, the software development process will be shown, as well as a baseline embedded solution. This contribution addresses the issue of limited computational capacity in embedded solutions and several ways to improve the performance and precision of the solver. Ultimately, a set of testing procedures, both onboard and model-based, will be developed for programs involving optimization schemes and non-linear variable time simulations.
La presente tesi di laurea magistrale è dedicata allo studio e allo sviluppo di algoritmi di ricarica intelligente ottimizzati per veicoli ibridi ed elettrici. Dopo avere introdotto l'architettura hardware e le infrastrutture coinvolte in tale funzione, verranno dettagliati i protocolli di smart charging per contestualizzare questo lavoro. Quindi, la complessità intrinseca del problema sarà formulata come un problema di ottimizzazione e diverse soluzioni saranno investigate per risolverlo. Verrà presentato un metodo sistematico per creare profili di ricarica ottimali per la funzione “Off-Peak”. Inoltre, verrà mostrato il processo di sviluppo del software e una sua applicazione pratica. Questo lavoro affronta il problema della capacità computazionale limitata dei calcolatori imbarcati nei veicoli e di come velocizzare e perfezionare la risoluzione. In definitiva, verrà sviluppata una serie di procedure di test, sia su veicolo che su modelli di simulazione, per software che coinvolgono schemi di ottimizzazione e soluzioni non lineari a tempo variabile.
Charging optimization method for electrified vehicles
BOULÉ, JULIEN JEAN-JACQUES PIERRE LUCIEN
2021/2022
Abstract
The present Master thesis is dedicated to the study and development of optimized smart-charging algorithms for hybrid and electric vehicles. After having described the hardware architecture and infrastructures involved in such a feature, smart-charging protocols will be detailed to set up the context of this work. Then, the inherent complexity of the problem will be stated as a constrained optimization problem and solutions to solve it will be investigated. A systematic method to build optimal solutions will be presented for the “Off-Peak” application. Additionally, the software development process will be shown, as well as a baseline embedded solution. This contribution addresses the issue of limited computational capacity in embedded solutions and several ways to improve the performance and precision of the solver. Ultimately, a set of testing procedures, both onboard and model-based, will be developed for programs involving optimization schemes and non-linear variable time simulations.File | Dimensione | Formato | |
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Charging_Optimization_Method_for_Electrified_Vehicles_2022.pdf
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https://hdl.handle.net/10589/186381