Home Program Author Index Search

CONTROL STRATEGIES FOR AUTOMOTIVE RANKINE SYSTEM EVALUATION USING A COSIMULATION PLATFORM


Go-down asme-orc2015 Tracking Number 86

Presentation:
Session: Poster session
Plenary session
Session start: 13:30 Tue 13 Oct 2015

Abdelmajid Taklanti   abdelmajid.taklanti@valeo.com
Affifliation: Valeo THermal Systems

Jin-Ming Liu   jin-ming.liu@valeo.com
Affifliation: Valeo THermal Systems

RĂ©gine Haller   regine.haller@valeo.com
Affifliation: Valeo THermal Systems


Topics: - System Design and Optimization (Topics), - Simulation and Design Tools (Topics), - Advanced Control Stratgies (Topics), - I prefer Oral Presentation (Presentation Preference)

Abstract:

Today, several solutions to recover wasted heat in automotive power train are considered and evaluated in order to reduce vehicle fuel consumption and to meet new emission regulation targets (El Habachi et al. (2010), Abbe Horst et al. (2014), Domingues et al. (2013) and Haller et al. (2014)). One of the solutions is to use Organic Rankine Cycle to recover waste heat from engine cooling system and/or engine exhaust gas and transform it to mechanical or electrical power. Automotive environment is very severe and very transient, the key point for operating such system is to set up and validate a suitable control strategy to maximize the recovered output power. In automotive industry development processes the control strategies are mainly described in a control tool environment. Commonly, the control is then tested and the control parameters are set up using physical mockups and prototypes of the studied system on a test bench. Afterwards the control is coded into a control unit and integrated in a vehicle or a demo-car in order to validate and tune up the control strategies and parameters. This process is very long and time consuming because physical prototype and demo-car are needed. In this paper, we are going to present a methodology using a virtual model of a R134a low temperature Rankine system integrated in a vehicle platform developed in a system simulation tool environment and coupled to a Rankine control system developed in a control tool environment. This methodology and co-simulation (see Taklanti et al., 2013) allow us to test and evaluate different control strategies, to select the optimal one and to set up control parameters prior to physical mockup or demo car availability. Finally, some results are presented showing the performance of a low temperature R134a Rankine system in a vehicle environment and the performance of a control strategy for constant velocities and transient driving cycles.