Multiparametric and multiobjective thermodynamic optimization of a spark ignition range extender ice
CHALLENGE - The current legislation pushes for the increasing level of vehicle powertrain electrification. A series hybrid electric vehicle powertrain with a small Range Extender (REx) unit – comprised of an internal combustion engine and an electric generator – has the technical potential to overcome the main limitations of a pure battery electric vehicle: driving range, heating, and air-conditioning demands. The design approach of the OEMs is usually rather conservative: parting from an already-existing ICE or components and adapting it for the REx application. The fuel efficiency potential of a one-point operation of the REx ICE is therefore not fully exploited.
SOLUTION - This article presents a multi-parametric and multi-objective optimization study of a REx ICE. The studied ICE concept uses a well-known and proven technology with a favourable production and development costs: it is a two-cylinder, natural aspirated, port injected, four-stroke SI engine. The goal of our study is to find its thermodynamic optimum and fuel efficiency potential for different feasible brake power outputs. Our optimization tool-chain combines a parametric GT-Suite ICE simulation model and modeFRONTIER optimization software with various optimization strategies, such as genetic algorithms, gradient based methods or various hybrid methods. The optimization task is a multi-parametric and multi-objective one, with a goal of finding the thermodynamic optima for a defined engine Pe variant in a single-point operation.
BENEFITS - The optimization results show a great fuel efficiency improvement potential by applying this multi-parametric and multi-objective method, converging to interesting short-stroke designs with Miller valve timings.