Performance Optimization of I
Performance Optimization of I - - 4 Gasoline 4 Gasoline Engine with Variable Valve Timing Using Engine with Variable Valve Timing Using
WAVE/iSIGHT WAVE/iSIGHT
Sean Li, DaimlerChrysler Sean Li, DaimlerChrysler
(sl60@
(sl60@dcx dcx.com) .com)
Charles Yuan, Engineous Software, Inc Charles Yuan, Engineous Software, Inc
([email protected])
([email protected])
Background
!
The purpose of this study is to achieve high engine performance targets at high engine speed without sacrificing the output torque at low ends.
" In engine rating, two engines are compared by their maximum power and maximum
torque.
" The shape of the torque vs. rpm curve is the same as that of volumetric efficiency (VE)
vs. rpm.
" Because the air-fuel ratio is almost constant for the fuel to be burned completely, the
air breathing characteristics of the engine determines the shape of the VE vs. rpm curve.
" The VE vs. rpm curve is primarily determined by
• Engine intake and exhaust port design
• Valve lift
• Valve timing
• Manifold geometry ( runner diameter, runner length, plenum volume)
• Manifold configuration
• The rest of the intake and exhaust system
" For the maximum power, the engine geometry must be designed to obtain high
volumetric efficiency at high engine speed ( power equals the torque multiplied by rpm). When the engine speed is too high, the mechanical friction increases rapidly, thus limits the engine performance.
2001 Production Engine And Our Target
!
The objective is to achieve high engine performance targets (high engine rating) without sacrificing the engine torque at low engine speed.
!
The challenge is to design the engine intake & exhaust system and variable valve timing to meet the design goal.
!
The engine is inline with four cylinder gasoline engine with variable valve timing.
Optimization Formulation
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Design variables consist of engine geometry parameters, valve lift scaling factors, and valve event timing.
" Total number of design variables: 25
!
Objective function is defined as the sum square of the errors between the designed and desired engine performance
!
The optimization problem is formulized as Find: X
LB<= X <= X
UBMin: F(X) = ΣΣΣΣ (bp – bpt)
2Subject to: g
i(X) <= 0.0
Where bp is the simulated brake power and bpt is the brake power target
Valve Lift Profile Scaling
!
The valve lift scaling is used to define the valve lift profile
" critical to engine performance
!
This is the original valve lift profile scaling.
Manifold Geometry
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The manifold geometry dominates the shape of the volumetric efficiency vs. engine speed.
!
This is the original intake manifold design.
2.4L Engine WAVE Model
Engine With Original Exhaust Manifold Engine With New Exhaust Manifold
iSIGHT / WAVE Integration Process
Input
Output WAVE template
iSIGHT
Integration Design
Exploration
iSIGHT Design Exploration Process
Integrate & Automate Define & Explore Monitor
TYPICAL DESIGN PROCESS Are
Requirements Satisfied?
Modify Design Parameters)
Execute Simulation Code(s)
Variables Constraints
Objectives
OPT DOE APX QEM
Task Plan
The Benefits of Automation & Integration
!
Earlier study has shown that by using iSIGHT, cycle time reduction due to automation and integration is
tremendous. More importantly, iSIGHT allows engineers focus on what’s important for them:
Engineering!
80% Routine
20% Creative
80% Creative
20% Routine
Cycle Time Reduction
time 20% Routine
80% Creative
Exploration Engines
Optimization
# Rule-based
# Exploratory (GA etc)
# Gradient-based
# Mixed Variable
Approx.
Models
# Taylor series
# Response Surface
# Variable complexity
Design of Experiment
# Central Composite
# Full Factorial
# Orthogonal Array
# Latin Hypercubes
# Parameter
# Database
Deterministic Methods Deterministic
Methods
Quality Engineering
# Monte Carlo
# Taguchi Robust Design
# Reliability Analysis
# Reliability-based Optimization
# 6-Sigma
Stochastic
Methods Stochastic
Methods
Technical Approach
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Scale the valve lifts. In this project, the valve lifts are design variables, which are constrained by preset upper limits.
!
Change the exhaust manifold configuration to reduce the exhaust gas interference among the adjacent cylinders. The manifold is changed from 4-1 configuration to a manifold of three 2-1 junctions.
!
Set the intake and exhaust manifold geometry, the valve timings at different engine speed, and the valve lift scaling factors as design variables. There are totally 25 design variables.
!
Because of the large dimension and high nonlinearity of the problem , It
is difficult to apply DOE techniques. Therefore, simulated annealing
method is utilized to explore the peaks and valleys in the design space,
and the modified method of feasible directions follows to accelerate the
search in the valleys.
Optimization Strategy (I)
!
Normalization of Design Variables
" Normalization of design variables can make the topology of the objective function more regular and reduce the level of nonlinearity of the problem
!
Local Optimization
" When the optimization is to modify a design what already in production, the initial design can be assumed to be close to the optimal. This is a local optimization problem. There are 10 optimization methods in iSIGHT for this kind of problem.
!
Global Optimization
" When the optimization is performed on a new design, the task is a global optimization problem. Global optimization is a challenging problem. There is no single algorithm which guarantees a global optimum. Thus, design space exploration is essential.
" In iSIGHT, the major tools for design space exploration are DOE, grid
search, and random search methods such as Monte Carlo simulation,
genetic algorithm, and simulated annealing.
Optimization Strategy (II)
!
Design of Experiments (DOE)
" Using DOE techniques, the effect of each design variable as well as their interactions
on the objective function can be studied.
" Critical parameters can be identified.
" When the objective is relatively smooth and of low order, a response surface can be
constructed with the DOE data. The response surface will be a good representation of the objective function.
" However, if the objective function is highly nonlinear, it will be difficult to construct a
response surface to catch the important features of the objective function.
" For current study, the DOE and RSM approach is not feasible.
Optimization RSM Simcode
Optimization Strategy (III)
!
Grid Search
" The design space is divided into many sub regions. Optimization is carried out in each
region. The global optimum is found by comparing local optima.
!
Random Search
" Monte Carlo simulation, genetic algorithm, and simulated annealing are powerful
design space exploration tools.
" MCS – Randomly simulate a design/process, given the stochastic properties of one
more random variables, with a focus on characterizing the statistical nature (mean, variance, range, distributions, etc.)
" GA – Works with a set of solutions called a population, with each population member
called an individual. An initial population is created, and the population at the start of an iteration is modified by replacing one or more individuals with new solutions, which are created either by combing two individuals (crossover) or by changing an individual (mutation). This procedure is inspired by the evolution of population of living organisms.
" SA
!
Search Accelerating
" The simulated annealing often encounter difficulties when search gets into a narrow
valley. In these regions, the local optimization methods are often very efficient and would help accelerate the convergence of the search.
Which Algorithm? - Interdigitation
No single class of optimization algorithm works best for all classes
of design problems
Exploratory
Numerical
Heuristic Optimization
INTERDIGITATION
! Numerical Methods are fast & efficient hill climbers
! Exploratory Methods avoid getting caught in local optima
! Knowledge Based Techniques use the engineers knowledge
Benefits of Using MMFD Technique
!
Modified of Method of Feasible Directions – ADS (Automated Design Synthesis) is a direct numerical optimization
technique used to solve constrained optimization problems.
It has the following features:
" Rapidly obtains an optimum design
" Handles inequality and equality constraints
" Satisfies constraints with high precision at the optimum
" It is a gradient-based numerical method
" X
q= X
q-1+ ã S
q• Where X
qis design variable vector
• S
qis usable/feasible search direction
• ã is 1-D search step
Benefits of Using Simulated Annealing Technique
!
The Simulated Annealing technique is modeled on the physical process of the annealing of solids. In the metallurgical industry, annealing is used to strengthen metals
" A solid is immersed in a heat bath at a temperature that melts it. Molecules are allowed
to move freely, taking on many different energy states.
" The temperature of the heat bath is cooled at a certain rate, called a cooling schedule,
to allow the molecules to arrange themselves in a low energy ground state.
" In this ground state, the molecules are arranged in a crystal lattice which has a
minimal system energy associated with it.
!
As an optimization method, simulated annealing is used to minimize an objective function
" When minimizing a function, any downhill step is accepted and the process repeats
from this new point.
" An uphill step may be accepted. Therefore, it can escape from local optima. This uphill
decision is made by the Metropolis criteria. Uphill criteria is a function of temperature.
High temperatures are more subject to uphill acceptance than low temperatures.
" As the optimization proceeds, the length of the steps decline and the algorithm closes
in on the global optimum.
" Since the algorithm makes few assumptions regarding the function to be optimized, it
is robust with respect to non-quadratic surfaces.
Brake Power Convergence History - Overall
SA
MMFD
Brake Power Convergence History – Best Design
SA MMFD
$ SA did a good job to find a good starting point, but it has limitations – for a long time, it finds no improvement.
$ MMFD find the global optimal.
Brake Power Convergence History – MMFD
$ Best Solution for SA: 3.021
$ Best Solution for MMFD: 0.118
Optimization Results: Engine Brake Power
Optimization Results: Engine Brake Torque
Conclusion
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The optimized engine brake power and torque are close to the targets.
!
A diffuser at the intake port will increase the gas static pressure, and reduce the gas velocity when it passes through the valve. This will reduce the gas flow loss especially at high engine speed.
!
In the new exhaust manifold configuration, the runner length of the 2-3 cylinders is kept short to maintain the catalyst light -off time, while the runner length of the 1-4 cylinders is optimized to avoid exhaust gas interference among the cylinders.
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The benefit of utilizing the design exploration engineer iSIGHT is clearly demonstrated: Without iSIGHT, it is very difficult to achieve what we have done.
!
The combination of Simulated Annealing and Modified Method of
Feasible Directions is a powerful tool for the optimization of complex
problems such as engine performance.
We Won PACE Award!!!
!
PACE ( P remier A utomotive Suppliers' C ontributions to
E xcellence) Award Winner: Presented by Automotive News and Cap Gemini Ernst & Young
!
Judges’ Citation
" Engineous ‘ software is changing the paradigm of product
development. Rather than a labor-intensive, risk-averse, manual computer-aided engineering process, iSIGHT transforms product development into an automated, time-saving exploratory process.
" iSIGHT solves design problems by taking elements of good
solutions and reshuffling them to find the best answer to a designer’s “what if” questions. Bt dramatically reducing tedious trial and error and testing functions, engineers will have more time for exploration and assessing risk of new design options.
" There are numerous benefits: Reduced product cost, more
effective use of engineering resources, improved profits and
enhanced global coordination – and above all,
easier innovation
." iSIGHT is an open software platform that integrates and automates
not only Engineous’ own software tools but also applications and databases form analytical tools already used by automakers globally.