Gianmarco D'Emilio
MODELLING AND CONTROL OF ALTERNATIVE HYBRID PROPULSION SYSTEMS FOR HIGH EFFICIENCY PASSENGER AND HEAVY-DUTY VEHICLES.
Rel. Angelo Bonfitto, Saulius Pakstys. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2024
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Abstract: |
As the global pursuit of sustainable mobility/transportation intensifies, the need for reducing emissions from conventional vehicles becomes crucial. This thesis addresses this imperative by exploring the integration of advanced energy storage and conversion systems within the framework of Energy Management System (EMS) for electric bus. In recent years, research in Hydrogen Fuel Cell as a source of energy has been growing more and more, especially for heavy transport vehicles such as city buses, and, in particular, coupled with batteries or supercapacitors to eliminate the problem of their slow dynamic response. This thesis is produced to describe, model, and simulate an alternative hybrid powertrain for city bus in order to maximize overall energy efficiency. For this purpose, key performance indicators, including energy efficiency and battery c-rate are evaluated under different operating conditions such as payload and driving cycles. In the initial section, a state-of-the-art analysis of the available technologies about Electric Vehicles is performed, starting from traditional ones (ICE-based) to vehicles with different energy storage technologies (Hybrid Electric Storage System, HESS) . It examines the main methodologies and architectures, showing the advantages and disadvantages of each. In the following, a pure electric bus is considered, where the powertrain is supplied by the combination of battery system and a supercapacitor (SC) pack, introduced to the system, in parallel to the battery allowing to fulfill the bus's overall power request reducing the stress experienced by the battery. A comparative analysis is carried out between different control strategies, starting from a rule-based controller (RBC) , which is later improved to adapt to different drive cycles (A-RBC) . Finally, a Fuzzy logic controller based is used. The results obtained show a decrease in the C-rate experienced by the battery, with a value of Root Mean Square that is 32.1% lower than the one obtained without the use of SC, which is corresponding to an extension of battery life. In the second part, a vehicle model based on fuel cell is described, which operates in charge sustaining mode and uses a smaller battery than that of the normal production vehicle (-83,3%). Two different control techniques, namely a rule based and a fuzzy logic, are explored for the HESS management, to improve efficiency. Finally, SC pack is introduced to support the battery as a power buffer, significantly reducing the stress to which it is subjected. This configuration allows limiting the C-rate experienced by the battery to a maximum acceptable value of less than 2C, reducing the total mass of the energy storage system by 1200 kg (-69%) with respect to the normal production vehicle battery. In conclusion the main findings of this activities are: •??In the powertrain configuration equipped with Battery and SC pack, 32,1% reduction in battery C-rate is achieved. •??In the powertrain configuration equipped with Battery, Fuel cell and SC pack, the total mass of the HESS is reduced by 1200kg (-69%), while maintaining the C-rate limited to a maximum value of less than 2C. The study highlights the significance of optimal energy management in addressing the challenge of improving the sustainability of electric buses and contribute valuable knowledge to the field of electric vehicle, offering a nuanced understanding of the synergies between different energy storage technologies for greener and more efficient urban transportation. |
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Relators: | Angelo Bonfitto, Saulius Pakstys |
Academic year: | 2023/24 |
Publication type: | Electronic |
Number of Pages: | 72 |
Subjects: | |
Corso di laurea: | Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica) |
Classe di laurea: | New organization > Master science > LM-25 - AUTOMATION ENGINEERING |
Aziende collaboratrici: | UNSPECIFIED |
URI: | http://webthesis.biblio.polito.it/id/eprint/31005 |
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