Design, Modelling, and Control of a Waste Heat Recovery Unit for Heavy-Duty Truck Engines

Transcription

1 Design, Modelling, and Control of a Waste Heat Recovery Unit for Heavy-Duty Truck Engines S. Trabucchi, C. De Servi, F. Casella, P. Colonna Milan, 13 th -15 th September 2017

2 Contents 1 Thermal sources for Waste Heat Recovery (WHR) ORC configuration and optimization Control system design and simulation Conclusions

3 Motivations 2 1. Actual potential for the WHR unit? 2. Cycle configuration: best trade-off between simplicity and efficiency? 3. Control issues related to the chosen configuration?

4 WHR unit design 3

5 Truck engine waste energy 4 EGR: ~ 10% of Q fuel T max ~ 400 C EXHAUST: ~ 25% of Q fuel T max > 300 C EGR and EXH interesting from thermodynamic and economical point of view! Diesel engine model tuned on experimental data from modern ICE: COOLANT: ~ 15% of Q fuel T max ~ 140 C η DE 42% W net = kw v cruise = 85 km h 1

6 WHR unit constraints 5 ORC can not affect η DE, fully add-on cruise conditions T EXH,up = 314 C T EXH,down = 265 C full cooling of EGR stream maximize cylinders charge exhaust heat recovery upstream or downstream of the ATU SCR minimum operating temperature is 200 C radiator cooling capacity not fully exploited in cruise conditions cooling water minimum temperature down to 70 C ORC condenser in series to engine radiator

7 Cycle design & optimization 6 exhaust (EXH) and EGR evaporators in parallel single pressure level working fluid: MM (simple siloxane) high molecular complexity, h blade and ω stable up to 300 C compact end efficient two stages axial turbine T cond = 85 C, fixed Innovative integrated design method: simultaneous optimization of cycle parameters and turbine geometry η is,turb not set a priori + *image taken from

8 7 Best cycle configuration Model assumptions and boundary conditions m EXH kg s m EGR kg s T EGR 400 C T EXH,up 314 C T EXH,down 265 C η is,pump 65 % ΔP P 0.01 Optimization results Source W mec Q EXH Q EGR p eva ΔT sh η is,turb kw kw kw bar C % EGR + EXH up EGR + EXH down EXH down

9 Dynamic modelling & control 8

10 Dynamic model 9 Whole powertrain system modeled in Modelica Turbomachinery: off-design performance predicted as function of β and ω = system inputs / control variables = gas connection between DE and WHR unit Plate Heat Exchangers (PHEs): preliminary static design; 1D finite volume model simplified off-design correlations

11 Control objectives 10 Control objectives > 5 1. max (W ORC ) 2. T max,orc < 300 C 3. T min,exh > 200 C 4. ΔT sh > 5 C 5. cavitation, limit on p max..but.. Control variables 2 1. evaporators split 2. pump speed nr. objectives > nr. degree of freedom

12 Set points optimization 11 Primary requirements: SCR safe operation organic fluid stability Controlled variables: T min,exh ΔT sh Set-points constrained optimization θ = m EGR m TOT

13 Control architecture 12 G s = Relative Gain Array Λ matrix based on 2 x 2 MIMO system process transfer function matrix G(s), to quantify mutual interaction Δ(ΔT sh )(s) δm EGR (s) ΔT scr (s) δm EGR (s) Δ(ΔT sh )(s) δm EXH (s) ΔT scr (s) δm EXH (s) = G 11(s) G 12 (s) G 21 (s) G 22 (s) Λ = λ 11 1 λ 11 1 λ 11 λ 11 with λ 11 = 1 1 g 12 g 21 g 11 g 22 decoupler disturbance λ11 = 2.5 statically decoupled centralized control architecture controllers process

14 Control limitations 13 Multivariable Right-Half-Plane transmission zeros analysis: process is non-minimum phase result of system design limitation on bandwidth for stability reason, ω c,max = 0.01 rad/s Ideal driving cycle = slow ramps good performance when system stressed at ω < ω c,max

15 Real drive cycle 14 Real driving cycle = fast ramps poor performance when system stressed at ω > ω c,max (disturbance faster than process!) T MM > 300 C = T MM,max primary control objective not satisfied fluid stability limit

16 Conclusions ORC power output at cruise speed is 4.8 kw roughly 5% of fuel saving 2. Best configuration: two evaporators in parallel, exhaust gas cooling upstream of the ATU 3. Simple PI-based control system not safe review of process design change of system dynamics adoption of more sophisticated control system system design control design

17 Thank you for your attention! 16