About the hand-in tasks. Vehicle Propulsion Systems Lecture 3. Outline. Energy System Overview. W2M Energy Paths. The Vehicle Motion Equation

Transcription

1 About the han-in tasks Vehicle Propulsion Systems Lecture 3 Conventional Powertrains with Transmission Performance, Tools an Optimization Lars Eriksson Professor Vehicular Systems Linköping University General avice Prepare yourselves before you go to the computer Make a plan (list of tasks) Han-in Format Electronic han-in Report in PDF-format Reasons: Easy for us to comment Will give you fast feeback March 21, / 48 3 / 48 Energy System Overview Primary sources Different options for onboar energy storage Powertrain energy conversion uring riving Cut at the wheel! Driving mission has a minimum energy requirement. 4 / 48 5 / 48 W2M Energy Paths The Vehicle Motion Equation Newtons secon law for a vehicle t v(t) = F t(t) (F a (t) + F r (t) + F g (t) + F (t)) Fa F Ft Fg Fr α mv g F t tractive force F a aeroynamic rag force F r rolling resistance force F g gravitational force F isturbance force 6 / 48 7 / 48 Mechanical Energy Deman of a Cycle Only the eman from the cycle The mean tractive force uring a cycle F trac = 1 xtot where = t max 0 v(t)t. Note t trac in efinition. Only traction. 0 Iling not a eman from the cycle. max(f (x), 0) x = 1 F (t)v(t)t t trac Evaluating the integral Tractive force from The Vehicle Motion Equation F trac = 1 2 ρ a A f c v 2 (t) + g c r + a(t) Resulting in these sums F trac = F trac,a + F trac,r + F trac,m F trac,a = ρ a A f c v 3 i h F trac,r = 1 g c r v i h F trac,m = 1 ā i v i h 8 / 48 9 / 48

2 Values for cycles Two Approaches for Powertrain Simulation Dynamic simulation (forwar simulation) Cycle Driver Engine Transm. Wheel Vehicle Numerical values for the cycles: X trac,a = 1 X trac,r = 1 X trac,m = 1 {MVEG-95, ECE, EUDC} v 3 i h = {319, 82.9, 455} v i h = {0.856, 0.81, 0.88} ā i v i h = {0.101, 0.126, 0.086} Ē MVEG-95 A f c c r kj/100km Normal system moeling irection Requires river moel Quasistatic simulation (inverse simulation) Cycle Vehicle Wheel Reverse system moeling irection Follows riving cycle exactly Transm. Engine 10 / / 48 QSS Toolbox Quasistatic Approach IC Engine Base Powertrain The [ Vehicle Motion ] Equation With inertial forces: + 1 J rw 2 w + γ2 J rw 2 e t v(t) = γ Te (Fa(t) + Fr (t) + Fg (t) + F(t)) rw Gives efficient simulation of vehicles in riving cycles 12 / / 48 Causality an Basic Equations Different Types of Gearboxes Causalities for Gear-Box Moels Quasistatic Approach ω1 T1 γ GB ω2 T2 Dynamic Approach ω1 T1 γ GB ω2 T2 Manual Gear Box Automatic Gear Box, with torque converter Automatic Gear Box, with automate clutch Automatic Gear Box, with ual clutches (DCT) Power balance Loss free moel Continuously variable transmission ω 1 = γω 2, T 1 = T 2 γ 14 / / 48 Connections of Importance for Gear Ratio Selection Vehicle motion equation: Gear ratio selection connecte to the engine map. t v(t) = F t 1 2 ρ a A f c v 2 (t) g c r g sin(α) Constant spee t v(t) = 0: F t = 1 2 ρ a A f c v 2 (t) + g c r + g sin(α) A given spee v will require power F t v from the powertrain. This translates to power at the engine T e ω e. Changing/selecting gears ecouples ω e an v. Require tractive force increases with spee. For a fixe gear ratio there is also an increase in require engine torque. Aitionally: Also geometric ratio between gears. i g,1 i g,2 ig,2 i g,3 ig,3 i g,4 ig,4 i g,5 16 / / 48

3 Gear-box Efficiency Optimizing gear ratio for a certain cycle. Potential to save fuel. Case stuy 8.1 (we ll look at it later). In traction moe T 2 ω w = e gb T 1 ω e P 0,gb (ω e ), T 1 ω e > 0 In engine braking moe (fuel cut) T 1 ω e = e gb T 2 ω w P 0,gb (ω e ),, T 1 ω e < 0 18 / / 48 Clutch an Torque Converter Efficiency Torque Characteristics of a Friction Clutch Friction clutch torque: T 1,e (t) = T 1,gb (t) = T 1 (t) t Action an reaction torque in the clutch, no mass. Approximation of the maximum torque in a friction clutch ) T 1,max = sign( ω) (T b (T b T a ) e ω / ω0 20 / / 48 Main parameters in a Torque Converter Input torque at the converter: T 1,e (t) = ξ(φ(t)) ρ h 5 p ω 2 e(t) Converter output torque T 1,gb (t) = ψ(φ(t)) T 1,e (t) Graph for the spee ratio φ(t) = ωgb ω e, an the experimentally etermine ψ(φ(t)) The efficiency in traction moe becomes η tc = ω gb T 1,gb ω e T 1,e = ψ(φ) φ 22 / / 48 Metho Quasistatic analysis Layout Average operating point metho Goo agreement for conventional powertrains. Han-in assignment. More etails an better agreement (epens on moel quality) Goo agreement for general powertrains Han-in assignment. 24 / / 48

4 Quasistatic analysis IC Engine Structure Quasistatic analysis Engine Operating Points 26 / / 48 Performance an riveability Important factors for customers Not easy to efine an quantify For passenger cars: Top spee Maximum grae for which a fully loae car reaches top spee Acceleration time from stanstill to a reference spee (100 km/h or 60 miles/h are often use) 28 / / 48 Top Spee Performance Uphill Driving Starting point The vehicle motion equation. t v(t) = F t 1 2 ρ a A f c v 2 (t) g c r g sin(α) At top spee t v(t) = 0 an the air rag is the ominating loss. power requirement (F t = Pmax v ): P max = 1 2 ρ a A f c v 3 Starting point the vehicle motion equation. t v(t) = F t 1 2 ρ a A f c v 2 (t) g c r g sin(α) Assume that the ominating effect is the inclination (F t = Pmax v ), gives power requirement: P max = v g sin(α) Improve numerical results require a more careful analysis concerning the gearbox an gear ratio selection. Doubling the power increases top spee with 26%. 30 / / 48 Acceleration Performance Maximum Engine Torque an Power Starting point: Stuy the buil up of kinetic energy 150 Power Torque 300 E 0 = 1 2 v 2 0 Assume that all engine power will buil up kinetic energy (neglecting the resistance forces) Average power: P = E 0 /t 0 Power [kw] Torque [Nm] A hoc relation, P = 1 2 P max Assumption about an ICE with approximately constant torque (also incluing some non accounte losses) P max = v 2 t Spee [RPM] 32 / / 48

5 Acceleration Performance Valiation Publishe ata an P max = mv v 2 t 0 34 / / 48 Optimization problems Different problem types occur in vehicle optimization Structure optimization Parametric optimization Control system optimization 36 / / 48 Driving cycle specification Gear ratio Path to the solution Implement a simulation moel that calculates m f for the cycle. Set up the ecision variables i g,j, j [1, 5]. Set up problem min m f (i g,1, i g,2, i g,3, i g,4, i g,5 ) s.t. moel an cycle is fulfille (1) Gears specifie but ratios free. How much can change gear ratios improve the fuel economy? Use an optimization package to solve (1) Analyze the solution. 38 / / 48 Moel implemente in QSS Structure of the coe Conventional powertrain. Efficient computations are important. Will use a similar setup in han-in assignment / / 48

6 Running the solver Running the solver Improves the fuel consumption with 5%. Improvements of 0.5% are worth pursuing. Complex problem, global optimum not guarantee. Several runs with ifferent initial guesses. 42 / / 48 PSAT Argonne national laboratory Different tools for stuying energy consumption in vehicle propulsion systems Quasi static Dynamic QSS (ETH) X Avisor, AVL X (X) PSAT X CAPSim (VSim) X Inhouse tools (X) (X) 44 / / 48 Avisor Avisor Information from AVL: The U.S. Department of Energy s National Renewable Energy Laboratory (NREL) first evelope ADVISOR in Between 1998 an 2003 it was ownloae by more than 7,000 iniviuals, corporations, an universities worl-wie. In early 2003 NREL initiate the commercialisation of ADVISOR through a public solicitation. AVL respone an was aware the exclusive rights to license an istribute ADVISOR worl-wie. 46 / / 48