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ScienceDirectEnergy Procedia 00 (2017) 000–000

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IV International Seminar on ORC Power Systems, ORC201713-15 September 2017, Milano, Italy

Method for designing waste heat recovery systems (WHRS) in vehicles considering optimal control

Philipp Petra*, Wilhelm Tegethoffa,b, Jürgen Köhlerb

aTLK-Thermo GmbH, Hans-Sommer-Str. 5, 38106 Braunschweig, GermanybTU Braunschweig, Institut für Thermodynamik, Hans-Sommer-Str. 5, 38106 Braunschweig, Germany

Abstract

In internal combustion engines, only a small part of the fuel’s chemical energy is transformed into mechanical energy. The residue is mainly wasted as thermal energy via the cooling system or as exhaust gas into the environment. In particular, the exhaust gas still has a high exergetic potential, which can be converted into mechanical energy by means of an Organic Rankine Cycle (ORC). Designing a waste heat recovery system (WHRS) for maximum benefit in transient operation is challenging. Interactions with vehicle subsystems, transient boundary conditions, major influence of the operating strategy on the performance and the complexity of the optimization problem must be considered. TLK-Thermo GmbH and the Institute of Thermodynamics at the TU Braunschweig develop a method and required software for the building blocks for the optimization of complex thermal systems: 1. Sensitivity analyzes to quantify the influence of system parameters on the system dynamics and the energy efficiency of the system. 2. Operating strategies for maximum energy efficiency. 3. Model-based control to ensure the best possible application of the previously determined operation. By means of developed method, a design concept of a waste heat recovery system for an omnibus is developed and tested in virtual test drives. The simulated fuel consumption saving potential leads from 5.6 % for the World Harmonized Vehicle Cycle (WHVC) to 8.0 % for a typical drive from Hanover to Munich.

© 2017 The Authors. Published by Elsevier Ltd.Peer-review under responsibility of the scientific committee of the IV International Seminar on ORC Power Systems.

Keywords: Design method, Organic Rankine Cycle, ORC, optimal operation strategies, waste heat recovery in vehicles, FMU, dynamic model

* * Corresponding author. Tel.: +49 531 390 76 260; fax: +49 531 390 76 29.E-mail address: p.petr@tlk-thermo.com

1876-6102 © 2017 The Authors. Published by Elsevier Ltd.Peer-review under responsibility of the scientific committee of the IV International Seminar on ORC Power Systems.

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1. Motivation for the development of a new method for designing waste heat recovery systems in vehicles

To maximize the fuel economy of utility vehicles with internal combustion engines like trucks and busses, waste heat recovery as well as the hybridization of the propulsion are the most promising measures. Since the exhaust gas temperatures of a diesel engine are up to approx. 600 °C, depending on the driving condition and the position in the exhaust system, the amount of usually unused exergy is worthwhile to recuperate. Figure 1 shows the principle and the nomenclature of the Rankine process considered in this study.

Fig. 1.: (a) principle and nomenclature of the considered Rankine Process; (b) temperature-enthalpy diagram of one operating point

Many publications cover the design and potential of waste heat recovery systems (WHRS) based on the Rankine Cycle (ORC) in vehicles ([1] - [8]). Nevertheless, the design of WHRS to exploit the maximum amount of exergy is challenging:

1. Interactions with adjoining systemsNumerous interactions with the internal combustion engine, the exhaust after treatment systems and potentially the cooling system must be considered ([1], [5]). A direct coupling of the mechanical energy obtained by the expander machine with the drive train reduces the load of the internal combustion engine. This in turn reduces the recuperated power of the ORC and must be considered when calculating the fuel saving potential of the vehicle. Some car concepts intend to convert the obtained mechanical energy into electrical energy ([1] and [5]) for decoupling the WHRS from the powertrain. However, since this exceeds the average required electrical energy, the full potential of the waste heat utilization system cannot be exploited without a hybridization of the powertrain. Due to legal requirements, the functionality of the exhaust after treatment system has priority over the WHRS. To ensure required minimum exhaust gas temperatures in the catalysts, the WHRS should be placed at the end of the exhaust system. As a result, the exergy flow rates decrease which reduces the benefit of the WHRS. Sophisticated, holistic control concepts enable a better positioning and thus higher recuperation potential. Re-cooling of working fluid condensation energy might be a bottle-neck in some operating conditions if it is transferred to the engine cooling system [9]. Dedicated condensers require additional installation space in the vehicle but could ensure functionality of both engine cooling and WHRS at high loads and ambient temperatures by decoupling the systems. Furthermore, the thermal efficiency of the WHRS is increasing with lower condensing temperatures depending on the used working fluid and restraints.

2. Transient exhaust enthalpy flow ratesTransient exhaust gas mass flow rates and temperatures require efforts on appropriate control and operating strategies for the ORC and adjoining systems. The operating strategy sets the target inlet state in the expander. The optimum setpoint provides maximum average exergetic efficiency and considers actual losses for all components.

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The control strategy effects the setpoints. It must handle varying dynamic behavior of the components and actuators in different operating conditions and the direction of load changes. Commonly assessed operating strategies consider only one constant setpoint for part load and nominal conditions. Depending on actual conditions, the setpoint cannot be realized because of low exhaust gas temperatures or mass flow rates. Therefore, the WHRS must be disabled to protect cycle components. Publications on optimal control strategies for ORCs are for example [10] – [16].

3. Major influence of boundary conditions and component losses on the optimum setpoints The selected optimization quantity is the exergetic system efficiency of the Rankine system. It is the product of exergetic efficiency of the evaporator (HX) and the exergetic efficiency of the Rankine process (ORC) itself. The first quantity describes how much of the exergy carried in the exhaust gas stream (ExhGas) is transferred to the working fluid (WF) in the evaporator, the second quantity describes the efficiency of the conversion of the exergy into the useful energy itself:

ηSystem=ηHX⋅ηORC=Δ EWF ,HXEExhGas

∗(PExp−PPump)Δ EWF , HX

=(PExp−PPump)

EExhGas (1)

The exergetic system efficiency is influenced both by the exhaust gas temperature and by the expander inlet state of the working fluid (pressure and enthalpy). For each exhaust gas temperature, there is a (different) inlet state in which the exergetic efficiency is maximal. In addition to the exhaust gas temperature, the optimum inlet state also depends on losses in the expander, in the heat exchangers (exergy losses due to heat transfer, pressure losses) and in the pump. To exploit the maximum recuperation potential, the adaption of the inlet state during the transient operation is indispensable. 4. Complexity of system optimization with dynamic modelsDesigning an optimal WHRS requires the optimization of a substantial number of structural parameters, for instance the working fluid, geometry parameters of the heat exchangers and the expander or the cycle configuration itself. For evaluation in transient test cycles, dynamic models and an adoption of the operating and control strategy are required. Consequently, the optimization problem could not be solved with simple optimizers.

Compared to the total amount of publications to ORC design, relatively few articles consider design optimization of WHRS with transient boundary conditions and optimal operational strategies, i.e. [4], [17] – [20]. In the authors opinion, no published approach covers satisfactorily all crucial factors for optimal design of vehicle WHRS.One of the aims of the joint work at TLK-Thermo and the Institute of Thermodynamics is the development of a method for the energetic optimization of complex and dynamic thermal systems. In this article, the method is described by the example of designing a WHRS for an omnibus. Transient boundary conditions, geometry parameter and operating strategy optimization are considered. The emphasis in this article lies on the improvement of fuel economy with optimized control strategies and the effect of constant setpoints on the component design.

2. Dynamic omnibus model and starting basis for the design of the WHRS

To illustrate the method, a dynamic model of an omnibus ([21], [22]) is developed in the modeling language Modelica based on the TIL and TILMedia model library [23]. The model comprises all relevant subsystems (see fig. 2). As basis for the conception, two vehicle cycles with more and less part load shares are used: The World Harmonized Vehicle Cycle (WHVC) and the European Transient Cycle (ETC). The boundary conditions for simulating the air-conditioning load are an ambient temperature of 24 °C, a relative humidity of 60 %, a solar irradiation of 500 W/m² and 28 passengers [24].

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Fig. 2: Modeled subsystems of the omnibus

Figure 3 shows simulated exhaust gas temperatures for the WHVC and the exergetic weighing of exhaust gas temperatures for the ETC and WHVC. The closer the positioning of the evaporator of the WHRS to the engine outlet, the higher but the more dynamic the exhaust gas temperatures. The exergetic weighing indicate the potential of adapting broad temperature ranges for the operation of the WHRS.

Fig. 3: (a) Exhaust gas mass flow rate and temperatures in the after-treatment system in the World Harmonized Vehicle Cycle (WHVC). (b) Exergetic weighting of occuring exhaust gas temperatures for the European Transient Cycle (ETC) and the WHVC

3. Method and used software tool chain

The method is illustrated in figure 4. To reduce the extent of the optimization problem, a pre-selection of promising parameter sets is necessary which are to be evaluated in transient simulations. In the first step, a simplified steady simulation model of the Rankine process is developed. The model parameters are the working fluid, efficiencies for the pump and the expander, pressure losses for tubes and heat exchangers and the pinch point

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temperature differences in the heat exchangers. The inlet state of the expander is optimized for maximum exergetic efficiency.

Fig. 4: Simplified sketch of the method for designing of a WHRS with maximum exergetic efficiency for vehicles. All steps are performed within a developed software tool box (MoBA Lab)

The simplified, fast models are used to evaluate the potential of the working fluid for specific exhaust gas and condensing temperatures. Beside required characteristic values for the cycle components, the sensitivity and dependency of component losses on the cycle performance or optimum inlet states can be evaluated for each working fluid. By means of calculated characteristics and the exergetic weighing of the heat source, promising working fluids can be selected. The evaluation could be adapted to other use cases by simply switching the exergetic weighing. The calculated characteristic values are also used to determine valid geometry parameters like tube cross section areas for the transient evaluation. The developed software tool chains automatize the evaluation.

The average performance of the selected parameter sets is assessed in transient vehicle simulations. The required dynamic models are first-principles Modelica models. The general control concept is shown in figure 5. It is based on feedforward and PID controllers. To maximize the system’s exergetic efficiency considering actual system characteristics, setpoints can computed online by means of the simplified model and actual sensor values.

Fig. 5: Control scheme of Rankine process. Setpoints and corresponding control variables (feed forward control) are computed online to maximize the exergetic efficiency of the Rankine Process

The core of the tool chain is the Functional Mockup Interface (FMI) standard ([25], [26]) which can be used to export models from a simulation environment such as Modelica / Dymola, Modelica / SimulationX or Matlab Simulink. The FMI standard allows to export a model from a simulation environment for the use in a different simulation environment. A special strength, however, is that FMUs (Functional Mockup Units) can be used and linked from dissimilar sources. The development of a subsystem can take place in Matlab Simulink, while another subsystem is developed, for example, in Modelica. The co-simulation or equation system interface can be used as required and limited by the coupling of the subsystems. At TLK-Thermo, the framework MoBA Lab is developed, in which mathematical analysis of the models (time constants, etc.), heuristics for the controller design, the solution of optimal control problems [10] as well as automated processing of simulation and evalutation tasks can be performed. Providing a Python interface, custom tasks can be adapted.

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4. Excerpt of the results of the preselection process with the steady high-speed model

In total, 32 different working fluids were investigated for 100 different exhaust gas temperatures, 5 condensing temperatures, 448 different component parametrizations and 2 cycle configurations were investigated, resulting in 448 000 optimization problems. Regarding the average exergetic efficiency, R-1233zd(E) for condensing temperatures below 40 °C, Cyclopentane up to 80 °C and Ethanol above 80 °C show the best performance. Differences in the sensitivities for component losses between the working fluids are noticeable. Following results are based on Cyclopentane as working fluid and a target condensing temperature of 60 °C

Influence of expander inlet state adaptionTo demonstrate the benefit of inlet state adaption, a constant setpoint is calculated for the WHVC as well as the ETC, which on average achieves the highest exergetic system efficiencies. It can be seen in figure 6 that the inlet state with the highest average recuperation potential differs depending on the cycle. Regarding the uncertainties of a real-world drive and the associated high fluctuations of the exhaust gas temperature and mass flow, the determination of only one setpoint for the design and control of the Rankine process leads to significant potential losses. An adaptation of the expander inlet state to the prevailing boundary conditions increases the exergetic system efficiency from 0.23 (optimized for WHVC) to 0.28 in the WHVC, respectively from 0.28 (optimized for ETC) to 0.32 in the ETC for given system parameters.

Fig. 6: Average exergetic system efficiency for the WHVC and the ETC for constant expander inlet states (Cyclopentane, T_Cond = 60 °C, η_Exp = 0.75, η_Pump = 0.5, ΔT_PinchPoint = 20 K). Variable setpoints increase the average efficiency around 21 % for the WHVC

respectively 13 % for the ETC in steady state simulations.

Effects of the operational strategy on boundary conditions for the evaporator and expander designFigure 7 shows target mass flow and volume flow rates calculated for the WHVC, plotted against the exhaust gas temperatures. Three different operational strategies are compared: Optimal setpoints, a constant setpoint optimized for the WHVC, and a constant setpoint optimized for high way use. For setpoints optimized for partial load, a substantial increase of the volume flow rate with increasing engine loads can be seen. Since the system efficiency in partial load operation is more sensitive to pressure losses than in full load operation due to physically induced limitations in heat transfer (location of the pinch point), undersized pipe cross sections can lead to a disproportionately inefficient process. On the one hand, the volume flow rate interval is low for the highway optimized operating strategy compared to the other strategies. On the other hand, operation at exhaust gas temperatures below 260 °C is not achievable which leads to several shut downs during the driving cycle. The optimal setpoint control shows more homogenous volume flow rates for exhaust gas temperatures between 150 and 280 °C, which enables stable process operation during the driving cycle.

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Fig. 7: Comparison of evaporator mass flow rate, volume flow rate and steady phase fraction in the WHVC for three different Rankine Cycle operational strategies, plotted against occurring exhaust gas temperatures.

5. Estimated fuel economy in virtual test drives

Evaporator geometry parameters of a fin and plate heat exchanger are optimized for maximum WHRS exergetic efficiency in numerous transient simulation studies by means of the developed tool chain and the dynamic Rankine Cycle and control models. Considering the major influence of the expander efficiency on the system efficiency and the range of volume flow rates in the cycle, we assumed that more than one expansion unit/stage is reasonable. Hence, expander efficiencies were set constant in the first step. This section summarizes the most important results of the full vehicle simulations with optimized process design and operational strategy. Virtual test drives were conducted in the WHVC, the ETC and a typical drive from Hanover to Munich on a typical 17th of August [24]. The influence of the WHRS on other subsystems is shown in figure 8. The recuperated power decreases the engine load in the WHVC by an average of 6.9 %. This reduces the exhaust gas temperature after the diesel oxidation catalyst by up to 19.7 K.

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Fig. 8 Simulation results of transient vehicle simulation without and with optimized Rankine system in the WHVC.

In the end, a fuel consumption saving of 5.6 % could be determined for the tested configuration in the WHVC. The comparison with the other rated cycles shows that the fuel economy increases with higher engine loads. In the case of the ETC with slightly higher loads, consumption savings amounts to 6.7 %, while the exemplary drive from Hanover to Munich is in the amount of 8.0 %. Figure 9 shows the fuel economy for the optimized cycle components with constant setpoints operation strategies. The potential improvement of an optimal setpoint control is up to 38 % [27].

Fig. 9: Simulated fuel economy of the Omnibus with optimized Rankine system with optimal setpoints and static setpoints for three drives

6. Summary

Developing a WHRS in transient boundary conditions for maximum exergetic efficiency is challenging because changes in system design parameters require an adaption of the control and operating strategy. There is no feasible software tool chain available, which cover all three building blocks for energetically optimized thermal systems: Sensitivity analyzes to quantify the influence of system parameters on the system dynamics and the energy

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efficiency of the system. Operating strategies for maximum energy efficiency. Model-based control to ensure the best possible application of the previously determined operating strategies. MoBA Lab and the developed high-speed and dynamic models cover the requirements.

In the preselection phase, substantial correlations could be identified. Direct evaporation, dedicated condensers, according to the case multiple expansion units and a hybridization of the propulsion are necessary factors for maximizing the fuel economy. Cyclopentane as promising working fluid also regarding to thermal stability could be identified. In transient cycle simulations, design parameters were optimized considering an adapted operating strategy to actual exhaust gas temperatures. Interactions with adjoining vehicle systems and the fuel economy potential are evaluated in virtual test drives. The maximum improvement was 8.0 % for Hanover-Munich, being at least 38 % higher than for a WHRS with fixed expander inlet states.

Acknowledgements

Parts of this publication have been developed with funding from the German Federal Ministry of Education and Research (BMBF) within the research project VEOS - Methodology for the energetic optimization of dynamic thermal systems (KMU Innovativ, 01 | LY1502)

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