This thesis proposes a new co-design optimization framework for the power- train sizing and control parameters of Plug-In Hybrid Electric Buses (PHEB). The PHEB must have the lowest powertrain Total Cost of Ownership (pTCO) while respecting a set of dynamic performances and lowering the equivalent consumption as much as possible. Previous works have addressed the prob- lem of powertrain sizing or control strategies independently but have failed to combine them in a multi-level system for heavy duty vehicles. In this thesis, the energy management strategy is nested within the plant design to create a system-level design in which the controller is optimized using the Equiva- lent Consumption Minimization Strategy (ECMS) for each plant evaluation computed using a Genetic Algorithm (GA). The GA implemented in Mat- lab performed simulations on a parallel configuration of PHEB simulated in Simulink, in which the power sharing factor was chosen according to the ECMS implemented in Matlab. The proposed co-design optimization suc- cessfully achieved better results than the conventional brute force search and proves that, compared to conventional Internal Combustion Engine (ICE) buses, PHEB manage to reduce both the consumption and the pTCO while meeting the same driving requirements.
|Datum Prijs||29 jun 2018|