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Model Predictive Control of the Electrical Powers on a H2-hybrid vehicle

azienda Thesis in external company    


Reference persons ALESSANDRO RIZZO

External reference persons Dr. Francesco Cianflone, Punch Torino

Description Thesis in company: Punch Torino https://www.punchtorino.com/
A H2-hybrid vehicle is considered, as composed by a H2 Fuel Cell System and a battery, that provide electrical powers in order to achieve what an E-drive motor is requiring to satisfy the engine torque requested by the driver. Optimal electrical power share is sought in order to minimize H2 consumption and maximize components lifetime, through a Model Predictive Control (MPC) strategy.

Given the optimization problem structure, including constraints, proper system models and input data coming from a co-simulation and/or experimental environment, the candidate should develop a tool (in Python, preferably) that is required to:

- Convert the optimization problem into a Quadratic Programming (QP) problem, by building the QP matrices

- Solve the QP optimization problem, by exploiting a proper algorithm

- Perform additional investigations, based on model predictions with the optimal sequence, such as a sensitivity analysis on MPC weights

Notes The thesis will be carried out at Punch, Torino. https://www.punchtorino.com/

Deadline 15/11/2021      PROPONI LA TUA CANDIDATURA

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