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Optimization of hybrid driveline configuration- Optimal component sizing to obtain the best possible fuel efficiency while maintaining performance characteristics

Manoj Ramesh
Göteborg : Chalmers tekniska högskola, 2018. Examensarbete - Institutionen för mekanik och maritima vetenskaper; 2018:08, 2018.
[Examensarbete på avancerad nivå]

Innovation is an important driving force in engineering and the goal of reducing emissions and creating a greener environment is pushing companies to create new technologies or improve existing technologies to achieve higher efficiency. Use of electric machines along with the standard powertrain in a vehicle can be defined as hybridization. Vehicle hybridization can be achieved in various levels, starting with the use of electric machines which aid starting and stopping of the vehicle all the way up to being able to drive the wheels. In order to achieve sufficient reduction in fuel consumption levels it is necessary to choose a balanced configuration of ICE and electric machines. This master thesis work deals with finding the optimum driveline configuration for passenger vehicles. Optimization of the hybrid driveline can lead to a solution of choosing a balanced configuration while maintain performance characteristics. Global optimization methods are used as optimization can be performed across ’n’ variables in the configuration. Heuristic algorithms require lesser computational power when compared other global optimization methods. These are optimization methods which employ a practical approach to a problem. Using Genetic algorithm (GA) an Nelder-Mead Simplex method (NM0 as the optimization strategies, simulations were performed across multiple drive cycles to obtain the optimum value of component sizes for Internal Combustion Engine, Electric Motor, number of cells in the battery pack, number of gears in each gear-box and also the respective gear ratios.

Nyckelord: Genetic Algorithm, Parallel Hybrid vehicles, Optimization, Component sizing, Quasi-Static Modeling



Publikationen registrerades 2018-12-05. Den ändrades senast 2018-12-05

CPL ID: 256376

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