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MODEL BASED CONTROL FOR WASTE HEAT RECOVERY HEAT EXCHANGERS RANKINE CYCLE BASE SYSTEM IN HEAVY DUTY TRUCKS


Go-down asme-orc2015 Tracking Number 191

Presentation:
Session: Session 16: Advance control strategies
Room: 1A Europe
Session start: 11:40 Wed 14 Oct 2015

Vincent Grelet   vincent.grelet@volvo.com
Affifliation: Volvo Trucks

Pascal Dufour   dufour@lagep.univ-lyon1.fr
Affifliation: UCBL1

Madiha Nadri   nadri@lagep.univ-lyon1.fr
Affifliation: UCBL1

Vincent Lemort   vincent.lemort@ulg.ac.be
Affifliation: ULG

Thomas Reiche   thomas.reiche@volvo.com
Affifliation: Volvo Trucks


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

Abstract:

Driven by future emissions legislations and increase in fuel prices engine gas heat recovering has recently attracted a lot of interest. In the past few years a high number of studies have shown the interest of energy recovery Rankine based systems for heavy duty trucks engine compounding [1]. Recent studies have brought a significant potential for such a system in a Heavy Duty (HD) vehicle, which can lead to a decrease in fuel consumption of about 5% and reduce engine emissions but many challenges still need to be faced before the vehicle integration. The system dynamics is mainly controlled by the heat exchangers behavior (i.e. evaporators and condenser) and dynamic models of these components are of two kinds: Moving Boundary (MV) and Finite Volume (FV). Both approaches have been widely used in large power recovery system and control system design [2] and results in a simplification of the heat recovery boiler/condenser geometry in a great extent (i.e. by representing the boiler by a straight pipe in pipe counterflow heat exchanger). The heat exchanger modeling methodology used in the following and its validation is approached in [3]. This paper presents a control oriented model development for waste heat recovery Rankine based control systems in heavy duty trucks. Due to the highly transient operating conditions, improving the control strategy of those systems is an important step to their integration into a vehicle. It is shown here that moving to more advanced control strategies than classical PIDs lead to some gains in terms of robustness and accuracy. Due to the limited availability and high operational cost of test bench the validation of such a controller is done on a representative and previously validated model [3].