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IV International Seminar on ORC Power Systems, ORC2017 13-15 September 2017, Milano, Italy The 15th International Symposium on District HeatingRankine and CoolingCycle The investigation of the Recuperative Organic models the wasteofheat recovery vehicles Assessing thefor feasibility using the heatondemand-outdoor
temperature function long-term heat demand forecast Mingru Zhao, Gequn Shu, for Hua aTian*, Fengyingdistrict Yan, Guangdai Huang, Chen Hu State Key Laboratory of Engines, Tianjin University, No. 92 Weijin Road, Tianjin 300072, China
I. Andrića,b,c*, A. Pinaa, P. Ferrãoa, J. Fournierb., B. Lacarrièrec, O. Le Correc a
IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal Abstract b c
Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France
Organic Rankine Cycle (ORC) has been valued for its promising application on the Waste Heat Recovery (WHR) from vehicles. And Recuperative ORC (RORC) is considered suitable for the on-board application because of its high efficiency. However, the previous investigations of RORC, which based on GT-suite, mainly focused on the steady state and didn’t consider the combined model with engine. In this paper, a Basic ORC (BORC) model and 3 RORC models with different recuperative rate are combined Abstract with engine model and compared. The steady state result shows that with the recuperative rate rising, the cooling heat decreases while the heating net output power increases, whichaddressed are beneficial the on-board application. However, thesolutions longer response time and District networks are commonly in thetoliterature as one of the most effective for decreasing the more chargedgas refrigerant mass arethe disadvantages. Also, compared BORC, backpressure andare performance of the engine greenhouse emissions from building sector. These systemswith require highthe investments which returned through the heat are basically notthe affected when recuperator is added. The transient responses show heat that demand with the in recuperative rising, the sales. Due to changed climate conditions and building renovation policies, the future rate could decrease, overshoot ofthe theinvestment temperature andperiod. output power of RORC become more serious at the start-up phase, which may cause prolonging return decomposition to of thethis refrigerant damage the expander. Atthe last, thedemand responses of combined modelsfunction under varying The main scope paper is and to assess the to feasibility of using heat – outdoor temperature for heat engine demand condition show that exhaust mass(Portugal), flowrate iswas mainly for the The engine backpressure variation. forecast. are Thestudied. districtThe of results Alvalade, located in Lisbon usedresponsible as a case study. district is consisted of 665 And RORC that withvary higher rate has more and advantages under heavy-duty condition. buildings in recuperative both construction period typology. Three weather engine scenarios (low, medium, high) and three district ©renovation 2017 The Authors. by Elsevier Ltd. intermediate, deep). To estimate the error, obtained heat demand values were scenariosPublished were developed (shallow, © 2017 The under Authors. Published by Elsevier Ltd. committee of the IV International Seminar on ORC Power Systems. Peer-review responsibility of the scientific compared with results from a dynamic heat demand model,ofpreviously developed and validated by the authors. Peer-review under responsibility of the scientific committee the IV International Seminar on ORC Power Systems. The results showed that when only weather change is considered, the margin of error could be acceptable for some applications Keywords: Waste Heat Recovery; Vehicles; RORC; GT-Suite; Pressure drop; Transient response (the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the 1.decrease Introduction in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the The growth in global energy demandcould has be been rising more the andfunction more inparameters recent years, poses significant coupled scenarios). The values suggested used to modify for thewhich scenarios considered, and improve the of heat demand estimations. challenges toaccuracy the sustainability. Internal Combustion Engines (ICE) used in transportation are responsible for a large © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * Corresponding author. Tel.: +86-15822683137. Cooling. E-mail address:
[email protected] Keywords: Heat demand; Forecast; Climate change 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.
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling.
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. 10.1016/j.egypro.2017.09.106
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part of energy consumption[1]. Naturally, new technologies have been developed to save energy. Among those technologies, Waste Heat Recovery (WHR) from ICE has been considered important and feasible. In particular, the Organic Rankine Cycle (ORC), as one of the solutions for WHR, has the advantages of less impact on the engine exhaust backpressure and higher energy conversion efficiency, compared with other technologies like turbocompounding and thermo-electric generation [2]. Research focusing on automotive ORC has increased in the last decade, and much progress has been made. Among these, companies like Cummins, Volvo, Renault Trucks, etc[3-5] and research groups such as ORNL, University of Liège, KTH, etc[6-7,17] have been investigating ORC with the one dimensional tool ——GT-Suite, which is already well spread out among the automotive industry for vehicle and engine simulations. With “Waste Heat Recovery” library implemented in the recent version, the steady or transient simulation of ORC are faster than many other computer codes[4], which attracts industries and system designers. Also, NIST Refprop is embedded as the refrigerant property data base. Considering the limited cooling capacity on vehicles, ORC is expected to have high efficiency [8], which means less cooling needs when outputting the same power. Therefore, some researchers focus on the Recuperative ORC (RORC), because of its high efficiency compared with the Basic ORC (BORC). Based on GT-Suite, Boretti [9] developed a RORC model and generally investigated the recovery of waste heat from the exhaust gases and the coolant of a 1.8 L gasoline engine. The RORC systems permit an increase in fuel conversion efficiency by up to 8.2%, at the steady-state. Then Edwards [6] used their RORC models to investigate the potential for efficiency improvement by recovering heat from the exhaust and EGR cooler of a light-duty diesel engine. Results from the steady state show that the efficiency of engine can be improved by 3.2%. However, the investigations about the RORC mainly focus on the steady-state results. Also, the combination with engine model requires more research for their transient interactive effect. So in this paper, a Basic ORC (BORC) model and 3 RORC models with different recuperative rate are combined with engine model, then compared under steady and transient state. All the ORC models are simplified for the investigative purpose. However, it’s worth mentioning that the control method is still under investigation. Therefore the properties of the ORC models are the main focus in this study. Nomenclature Pnet Pexp Ppump Qevap Qcond 𝜂𝜂 𝜆𝜆 𝜏𝜏
Net output power (kW) Output power from expander (kW) Consumed power by pump (kW) Absorbed heat in the evaporator (kW) cooling heat in the condenser (kW) Thermal efficiency (%) Friction coefficient Time to reach steady state at start-up phase (s)
2. Model description 2.1. The diesel engine model The engine model is calibrated against the experimental data from a heavy-duty diesel engine. It’s manufactured by Yuchai Group, and widely used on the long-haul heavy duty trucks which are very likely to apply WHR techniques. The engine parameter is listed in the Table 1. The engine model is made up of the inlet-and-exhaust system, injector, cylinder, crank train and turbo-charger based on GT-Suite. After calibration by the experimental data, the precision of the engine model is high enough for the following research. Table.1 Engine parameters Engine type
YC6L330-40(L6200)
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Intake system
Turbo-charger/Intercooler
Cylinder number
6
Cylinder diameter
113 mm
Piston stroke
140 mm
Total displacement
8.424 L
Compression ratio
17.5:1
Rated power
240 kW
Rated speed
2200 rpm
3
2.2. The ORC model The ORC systems use R245fa as the refrigerant. This refrigerant was widely chosen [3-5] based on its thermophysical properties over the expected operating range of ORC and the fact that it is non-toxic, non-flammable, and has low global-warming potential. The saturation pressure of R245fa at 25℃ is approximately 1.5 bar allowing for a low pressure in an air-cooled condenser on board. This low pressure and the high molecular weight of the refrigerant are important for extracting as much energy as possible in the expander [10]. Previous study by Yang [11] shows that R245fa owns the best performance for diesel engine waste heat recovery, compared with several HFO refrigerants and HC refrigerants. Based on the “Waste Heat Recovery” library in GT-Suite, the investigative ORC models are made up of the Heat Exchangers (including Evaporator, Condenser, Recuperator), Pump, Expander and other parts. Then the engine models and ORC models are connected as shown in Fig 1. Diesel Engine
Exhaust Gas
Diesel Engine
Exhaust Gas
Evaporator
Evaporator
Pump
Recuperator
BORC Pump
Condenser Receiver
Coolant
Expander
Expander
RORC Condenser
Receiver
(a)
Coolant
(b)
Fig. 1. (a) BORC model; (b) RORC model;
(1) Heat Exchanger: The heat exchanger models use already implemented counter-flow plate heat exchanger model, because of its compact structure, light weight and high efficiency on heat transfer [8]. The geometry of heat exchangers are designed and calculated by the common procedure. Different sizes of recuperator are designed and directly added in the BORC. The geometry of heat exchangers are listed in Table 2. On the refrigerant side, heat transfer coefficients are defined by implemented correlations. After several attempts, it turns out that the Kandlikar-GTI-Mod-Plate correlation [12] was the most stable correlation in ORC simulations for two-phase area in the evaporator, while the condenser uses Yan-Lio-Lin-Plate correlation [13] for two-phase area. For the pure liquid and vapor phase, the well-known Dittus-Boelter correlation [14] is adopted. Also, the pressure drop on the refrigerant side is neglected, since the accurate correlation for the two-phase area pressure drop in the plate heat exchanger is unavailable in the literature.
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Table.2 The geometry of heat exchangers BORC
RORC1
RORC2
RORC3
Evaporator Length(mm)
760
Width(mm)
700
Total Channel Numbers
20
Channel Height(mm)
3 (refrigerant side), 6 (gas side)
Chevron Angle
60°
Condenser Length(mm)
724
Width(mm)
700
Total Channel Numbers
40
Channel Height(mm)
3
Chevron Angle
60°
Recuperator Length(mm)
-
109
229
412
Width(mm)
-
100
200
300
Total Channel Numbers
-
Channel Height(mm)
-
3
Chevron Angle
-
60°
20
On the gas side, the most important object is “Pressure drop”, which affects backpressure of engine therefore becomes the key parameter of the combined model. The following pressure drop correlation is recommended for the hot air in the plate heat exchanger [15]. Δ𝑃𝑃 = 42400 ∙ 𝜌𝜌 ∙ 𝑣𝑣 ∙ 𝑅𝑅𝑅𝑅 −0.545
(1)
Where: 𝜌𝜌 means the gas density (kg/m3); 𝑣𝑣 means the gas velocity in the plate channel. (2) Expander and Pump The Expander and Pump models are the simple positive displacement, volumetric efficiency based models, which are designed for the organic fluids. The isentropic efficiency of pump and expander is all set as 80%, which is the default value in the template. It’s higher than the actual machine, however tolerable for the investigative research. During the whole test, the pump and expander speed are kept constant to simplify the comparison. (3) Net output power and thermal efficiency The following functions representing net output power and thermal efficiency are added in the models. 𝑃𝑃𝑛𝑛𝑛𝑛𝑛𝑛 = 𝑃𝑃𝑒𝑒𝑒𝑒𝑒𝑒 − 𝑃𝑃𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝 𝜂𝜂 =
𝑃𝑃𝑛𝑛𝑛𝑛𝑛𝑛
𝑄𝑄𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒
(2) (3)
2.3. The soundness verification of ORC models Since the test bench is under construction, the experimental data is unavailable for the model calibration. The suitable experimental results in literature are hard to obtain, either. However, the soundness verification is conducted in this article, based on the tutorials of GT-Suite [16-17]. As suggested in the tutorial, the temperature difference between refrigerant and wall in the two-phase section should be no more than 25% of the total temperature difference between refrigerant and heating/cooling source. In this model, the maximum temperature differences between wall and refrigerant in the two-phase section are 11.65% (evaporator) and 23.4% (condenser). Therefore, the heat exchangers in this model are properly set up.
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Then, the cycle needs to obey the mass and energy conservation. The maximum differences between the initialized mass and the final mass in all the refrigerant cycle are below 1%, which are much lower than the limit in the tutorial (5%). Also, the energy conservation in Eq(4) should be met. At all the refrigerant cycle, the maximum energy difference is 0.13kW, which is tolerable considering the energy loss in the pipes. (4)
𝑄𝑄𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 + 𝑃𝑃𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝 − 𝑃𝑃𝑒𝑒𝑒𝑒𝑒𝑒 − 𝑄𝑄𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 ≈ 0
So, the soundness verification proves that the models are available for the investigative research.
(a)
(b)
Fig. 2. Temperature curves in (a) Evaporator; (b) Condenser;
3. Results and discussion 3.1. The steady state results With different sizes of recuperator added in, the steady performances of RORCs were firstly analyzed and compared with BORC under the rated condition of engine (2200rpm, 100%load). The exhaust temperature and mass fowrate are 491℃ and 1273 kg/h separately. The simulations automatically stop when the steady states are met. The results are shown in Table 3. The difference rates δ of every RORC based on BORC are also calculated in the table and plotted in the Fig 3(a). Table.3 The comparison of steady state results BORC RORC1
RORC2 34.51%
δ2
RORC3 53.29%
δ3
Recuperative rate
0%
τ
56.7 s
57.3 s
1.06%
59.8 s
5.47%
63.6 s
12.17%
20.12 bar
20.87 bar
3.73%
21.72 bar
7.95%
22.73 bar
12.97%
Pevap
17.27%
δ1
Tevap
163.8℃
169.74℃
3.63%
181.3℃
10.68%
192.72℃
17.66%
Pnet
14.8 kW
15.54 kW
5%
16.44 kW
11.08%
17.43 kW
17.77%
Qevap
111.71 kW
109.98 kW
-1.55%
108.14 kW
-3.2%
105.93 kW
-5.17%
Qcond
96.96 kW
94.47 kW
-2.57%
91.79 kW
-5.33%
86.2 kW
-11.1%
Recuperative heat
-
4.88 kW
-
11.27 kW
-
19.68 kW
-
𝜂𝜂
13.25%
14.13%
6.64%
15.2%
14.72%
16.46%
24.23%
Refrigerant mass
22.76 kg
23.37 kg
2.68%
24.35 kg
6.99%
27.53 kg
20.96%
Backpressure
12.98 kPa
13.05 kPa
-
13.15 kPa
-
13.26 kPa
-
Engine Power
239.603 kW
239.596 kW
-
239.589 kW
-
239.574 kW
-
As we can see, when the recuperative rate varies from 0% to 53.29%, the cooling heat decreases while the net output power and thermal efficiency increase. That usually makes RORC suitable for the on-board waste heat recovery, since the cooling capacity is limited on vehicles [18]. Also in Fig 3(b), the effects on the backpressure of engine are almost the same (from 12.98kPa to 13.26kPa), because the evaporators in BORC and RORCs share the same structure. As a result, the engine power in these combined models differs in a negligible amount (from 239.574kW to 239.603kW).
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Most importantly, in Fig 3(a), all the parameters change in the diverging speed, with the recuperative rate rising. As with the cooling heat and the net output power, it’s beneficial for the application on board. However, the increasing τ and charged refrigerant mass will be the penalties. Because the larger τ means the longer response time to the varying engine condition. And also, more weight (including recuperator) on board will balance out the benefits from the waste heat recovery. In fact, the charged refrigerant mass changes in a fastest speed among all the parameters. This is important for designing the waste heat recovery system for the vehicle. The designer should weigh the factors and compromise as needed. 13.4
τ Pevap Tevap Pnet Qevap Qcond η m
240.8
13.3
0
Backperssure(kPa)
240.4
Engine power(kW)
13.2
240.0 13.1 239.6
Engine power(kW)
δ(%)
10
Reference Power (engine only)
Backperssure(kPa)
20
13.0 -10
239.2 12.9 0
10
20
30 40 Recuperative rate(%)
(a)
50
60
0
10
20
30
40
Recuperative rate(%)
50
60
(b)
Fig. 3. (a) The difference rates δ; (b) The backpressure and power of engine;
3.2. The transient response comparisons 3.2.1. The start-up phase
(a)
(c)
(b)
(d)
Fig. 4. (a) Expander inlet temperature; (b) Net output power; of BORC and RORC models (c) Backpressure; (d) Power; of engine
In the start-up transient test, the engine condition is still fixed at rated condition, of which the exhaust gas can be seen as constant during the whole test. From the comparison of τ in last part, the start-up of RORCs are a little lower than that of BORC. That’s because, with the recuperator included, the internal volume of the cycle and the charged
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refrigerant mass become larger. Therefore it has larger thermal inertial, also takes more time for the refrigerant to be pumped around the whole cycle. In Fig 4(a), the flat top of the temperature curve is because that, in GT-Suite, the temperature of every refrigerant is limited by its possible decomposition temperature in the Refprop data base. The over-limit temperature will be suppressed by the limit value. And the properties will be evaluated based on that. From the figure, the overshoot of the temperature in RORCs is more serious than that in BORC, which brings higher possibility of refrigerant decomposition. The reason is that the recuperator increases the evaporator inlet temperature. As the result in Fig 4(b), the overshoot of the output power in RORCs lasts longer and is stronger than that in BORC. With the recuperative rate rising, the vibration even shows up in RORC3. This may cause damage to the expander, if not controlled. At last, the backpressures from RORCs have negligible differences compared with BORC, in Fig 4(c). The largest difference (1.2kPa) happens between RORC3 and BORC at 12.3s. This small value almost makes no difference in the engine performance, as shown in Fig 4(d). 3.2.2. The response to the varying engine condition %
100
Speed & Torque
Speed Torque
80
60
40
0
50
100
150
Time (s)
(a)
200
250
300
(b)
(c)
(d)
Fig. 5. (a) Varying speed and torque; (b) Exhaust properties and backpressure; of engine (c) Net output power; (d) Cooling heat; of BORC and RORC models
Then the transient response of the combined models under varying engine condition are investigated. As shown in Fig 5(a), the maximum speed and torque of the engine is set as 100%. During the simulation of the first 150s, the torque, representing the load, is maintained almost unchanged within 97% to 99%. The speed is kept at 63.6%, 72.7% and 81.8% respectively for 50s. During the last 150s, the speed is kept constant, while the torque is changed to 79.6, 59.5% and 38.7% for every 50s. As shown in the Fig 5(b), the backpressure from ORC models is close to each other during the whole 300s, which will lead to the similar result on the engine performance. Also, the comparison among exhaust temperature, mass flowrate and backpressure shows that the exhaust mass flowrate is mainly responsible for the backpressure variation.
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Apart from the overshoot in the start-up phase, the net output power and the cooling heat of BORC and RORCs have obvious differences during the middle period from 32.4s to 204.6s. The largest differences are 2.2kW and 15kW respectively. Clearly, the middle period is the time that engine works under a heavy duty condition, where the cooling ability reaches the margin [18]. Higher output power with less cooling needs just meet the requirement. Therefore, for trucks that work mostly under heavy duty conditions, RORC with high recuperative rate may have more advantages. 4. Conclusions In this paper, a Basic ORC (BORC) model and 3 RORC models with different recuperative rate are combined with engine model. The conclusions from the steady state and transient response comparisons are shown as below: (1) The steady results show that with the recuperative rate rising, the cooling heat decreases while the net output power increases, which are beneficial to the on-board application. However, the larger τ and more charged refrigerant mass are disadvantages. In fact, all these parameters change in a diverging speed when recuperative rate rises. (2) The backpressure and performance of the engine are basically not affected when the recuperator is added. (3) The transient responses show that with the recuperative rate rising, the overshoot of the temperature and output power of RORC become more serious at the start-up phase, which may cause decomposition to the refrigerant and damage to the expander. The responses of the combined models under varying engine condition show that, exhaust mass flowrate is mainly responsible for the backpressure variation. And RORC with higher recuperative rate has more advantages under heavy-duty engine condition. Acknowledgements This work was supported by The Natural Science Foundation of China (No. 51676133). The authors gratefully acknowledge them for support of this work. References [1] International Energy Agency. World Energy Outlook 2015. London, 10 November 2015. [2] Gequn Shu, Mingru Zhao, Hua Tian*, Yongzhan Huo, Weijie Zhu. Experimental comparison of R123 and R245fa as working fluids for waste heat recovery from heavy-duty diesel engine. Energy 115 (2016) 756-769. [3] Cummins, Inc. Development of an Exhaust Energy Recovery System Model. Gamma Technologies North American User’s Conference. [4] N. Espinosa, I. Gil-Roman, D.Didiot, V. Lemort, B. Lombard and S. Quoilin. Transient Organic Rankine cycle Modelling for Waste Heat Recovery on a Truck. ECOS 2011. [5] N. Espinosa,L. Tilman,V. Lemort,S. Quoilin,B. Lombard. Rankine cycle for waste heat recovery on commercial trucks: approach, constraints and modelling. Diesel International Conference & Exhibition, 2010. [6] K. Dean Edwards, Robert M. Wagner. Investigating potential fficiency improvement for light-duty transportation applications through simulation of an Organic Rankine Cycle for waste-heat recovery. ICEF 2010. [7] Fernando Rojas Tena, Reber Kadir. Waste Heat Recovery Modelling[D]. KTH Industrial Engineering and Management, 2011. [8] Christopher R. Nelson. Application of refrigerant working fluids for mobile Organic Rankine Cycles. Paper ID: 41. 3rd International Seminar on ORC Power Systems, October 12-14, 2015, Brussels, Belgium [9] Alberto Boretti. Recovery of exhaust and coolant heat with R245fa organic Rankine cycles in a hybrid passenger car with a naturally aspirated gasoline engine. Applied Thermal Engineering 36 (2012) 73-77. [10]https://www.honeywell-refrigerants.com/americas/product/genetron-245fa/. [accessed 17.05.06] [11]Fubin Yang, Hongguang Zhang, Songsong Song, Chen Bei, Hongjin Wang, Enhua Wang. Thermo-economic multi-objective optimization of an organic Rankine cycle for exhaust waste heat recovery of a diesel engine. Energy 93 (2015) 2208-2228. [12] Donowski, Vincent D., and Satish G. Kandlikar. “Correlating evaporation heat transfer coefficient of refrigerant R-134a in a plate heat exchanger.”, Engineering Foundation Conference on Pool and Flow Boiling, Alaska. 2000. [13] Yan, Y. Y., Lio, H. C., & Lin, T. F.. Condensation heat transfer and pressure drop of refrigerant R-134a in a plate heat exchanger. International Journal of Heat and Mass Transfer (1999), Volume 42, Page 993–1006. [14] Frank P., DeWitt, David P. Fundamentals of Heat and Mass Transfer (6th ed.)[M]. New York: Wiley. p.514. 2007. [15] Lichen Wang. Design and Simulation of saving energy system for dry process of dyeing fabric[D].China Jiliang University, 2013. [16] Gamma Technologies.Air Conditioning and Waste Heat Recovery Tutorials. 2013. [17] Songsong Song, Hongguang Zhang, Fubin Yang, Chen Bei. The performance analysis of Organic Rankine Cycle based on GT-Suite. ACTA ENERGIAE SOLARIS SINICA, V0l.37, No.6,Jun,2016. [18] N. Espinosa, L. Tilman, V. Lemort, S. Quoilin, B. Lombard. Rankine cycle for waste heat recovery on commercial trucks: approach, constraints and modelling. Diesel International Conference and Exhibition, 2010.