Fuel consumption potential of different external combustion gas-turbine thermodynamic configurations for extended range electric vehicles

• Published in: Energy (Oxford) 2019-05, Vol.175, p.900-913
• Main Authors: Reine, Alexandre, Bou Nader, Wissam
• Format: Article
• Language: English
• Subjects: Auxiliary power units; Classification; Combustion; Computer simulation; Configurations; Converters; Dynamic programming; Electric vehicles; Energy; Energy conversion efficiency; Energy management; Environmental Sciences; Extended-range-electric-vehicle; External combustion gas-turbine; Fuel consumption; Gas turbines; Genetic algorithms; Hybrid electric vehicles; Internal combustion engines; Light duty vehicles; Non-dominated sorting genetic algorithm; Operating temperature; Optimization; Powertrain; Sorting algorithms; Technological analysis; Weight
• ISSN: 0360-5442; 1873-6785
• DOI: 10.1016/j.energy.2019.03.076

External combustion gas-turbine (ECGT) systems are among potential multi-fuel energy converters to substitute the internal combustion engine (ICE) as auxiliary power unit (APU) in future extended range hybrid electric vehicle (EREV) powertrains. Fuel consumption of these APUs in EREV strongly relies on the energy converter efficiency and power to weight ratio as well as on the energy management strategy deployed on-board. This paper presents a technological analysis and investigates the potential of fuel consumption savings of an EREV using different ECGT-system thermodynamic configurations. These include a simple ECGT (S-ECGT), a downstream simple ECGT (DS-ECGT), a downstream intercooled ECGT (DS-ECGT) and a downstream intercooled reheat ECGT (DIRe-ECGT). An energetic and technological analysis is conducted to identify the systems’ efficiency and power to weight ratio for different operating temperatures. An EREV model is developed and the different ECGT-system configurations are integrated as APUs. A bi-level optimization method is proposed to optimize the powertrain. It consists of coupling the non-dominated sorting genetic algorithm (NSGA) to the dynamic programing (DP) in order to minimize the fuel consumption and the number of switching On/Off of the APU, which impacts its durability. Fuel consumption simulations are performed on the worldwide-harmonized light vehicles test cycle (WLTC). Results show that the DIRe-ECGT-APU presents an improved fuel consumption compared to the other investigated ECGT-systems and a good potential for implementation in EREVs. •Study assesses the fuel consumption of different external combustion gas-turbine system for hybrid vehicles.•Technological analysis and thermodynamic optimization are conduced to identify the efficiency and power to weight ratio.•Vehicle fuel consumption are performed using a bi-level optimization method as energy management strategy.•Downstream-intercooled reheat external combustion gas-turbine system is prioritized.