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Speakers Information - Controls, Measurement & Calibration Congress
Author: Seetareddy Beeravalli Version: V1.0 Page 1
Concept Development for Complex EMS Application Using Matlab Simulink – A Case Study
Mr.Seetareddy Beeravalli Senior Technical Specialist
Powertrain Engine Systems, Continental Automotive Components (India) Pvt. Ltd
ABSTRACT
In automotive industry, increasing complexity of system driven by stringent emission standards is leading to development of more complex functions. One of the proven technologies for performance improvement, emission reduction is the variable valve timing (VVT). In this paper, development of an algorithm to control VVT integrated with mid-lock pin is discussed in the context of efficiency brought by employing model based development method. This development was driven by certain drawback associated with existing VVT system, the new system is designed to achieve lower emission at transient conditions like cold start wherein emission is higher than at normal operating conditions. The model based development proved very useful in terms of development and validation, and to reduce the time to market.
Author: Seetareddy Beeravalli Version: V1.0 Page 2
INTRODUCTION
Automotive OEMs are focusing on improving the systems associated with combustion and emission control in order to meet the emission norms apart from achieving fuel efficiency to have a bigger market share. The time to market for new systems is shrinking due to competition, which demands that new systems are designed, developed and validated in less time, and in a robust way.
In the existing VVT system, greater intake phasing is needed to further improve part-load fuel economy and to reduce emission, but in-turn this will lead to startability problem. This gap in VVT operation is bridged by introducing a new hardware with additional lock pin in the mid-position of VVT range that has to be controlled based on engine operating conditions using digital actuator. This system needed an algorithm to work with new hardware as well as support the old configuration for vehicles that are running with conventional VVT system.
In general, algorithm development for new concepts takes multiple loops to refine the solution and rectify defects. This needs a development method to cover all facets of operating environment with extensive requirement engineering. To reduce the risk of errors and time for development, model based approach is used for this concept development. Using MBD, the number of loops required to arrive at a refined solution is reduced. The MBD gives a platform to validate the behavior before integrating with the HW system.
The hardware requirement and control strategy was analyzed and the design is conceptualized. Algorithm is designed in SDA (System Design Automation) [3], which is based on Matlab-Simulink© (SDA is the MBD platform used at Continental Engine System - figure 1). The new VVT solution consists of several modules interacting with other functions as well as the new hardware. The VVT concept algorithm is simulated to observe whether expected behavior is attained with the test vectors. Any deviation in the simulated behavior points to deviation in the solution identified for requirement. With solution frozen, the model is tested with scaled model (from floating point to fixed point) and verified using existing test vectors. SW code is generated out of the model using Embedded Coder©, and verified using defined test vectors to check whether software works as intended via SIL (Software In the Loop) mode (where generated code will be part of Matlab environment as S-function). To verify that the code works as expected in the target environment, generated code is compiled with target compiler and will be simulated via PIL (Processor In the Loop) mode and executed on a target simulator. The function behavior should be same in all the modes of simulation. MBD helps by guidance at each stage of development to verify function behavior and rectify problems before progressing to next stage of development.
Figure 1 - Integrated MBD environment at Continental [3]
Author: Seetareddy Beeravalli Version: V1.0 Page 3
MAIN SECTION
VARIABLE VALVE TIMING:
The variable valve timing is also referred as variable cam phasing (VCP). The mechanism behind this system is to phase the angle of opening/closing of inlet/exhaust valves with respect to crankshaft position. In other words, it is possible to change the closing point of the inlet valves and/or the closing point of the exhaust valves.
The VVT influences the gas exchange process. The torque characteristics dependent on the engine speed and load can be modified. The closing point of the inlet valves can be optimized for inertial and wave effects of the air flow in the intake manifold, i.e., for increasing the air flow into the combustion chamber. Especially the phasing of the exhaust camshaft can be used for the internal exhaust gas recirculation. It has effects on the emission production, torque and fuel efficiency. Further, VVT can have effects on the wall film behavior in multi-port injection engines.
The phasing is achieved by controlling engine oil flow into cam phasing chambers using solenoid valves. The set-point for the valve timing is decided by the engine operating condition and the feedback circuit is established by cam and crank sensors.
SYSTEM SCHEMATIC:
Figure 2 - Variable Cam phasing actuator hydraulic ring
Chamber A Chamber B
Figure 3 - Cam phasing device
Author: Seetareddy Beeravalli Version: V1.0 Page 4
Drive from
crankshaft
Adjustment
angle
Cam
CamshaftA B
Oil line
to B
Oil line
to A
Rotor
Stator
Figure 4 - VCP actuator principle
Pres
suriz
ed o
il P
Oil li
ne to
cha
mbe
r B
Oil li
ne to
cha
mbe
r A
Outfl
ow to
oil p
an O
Outfl
ow to
oil p
an O
Solenoid
Spring
Control piston Stick
Holding, 50% PWM
Adjustment, 100% PWM
B A
Adjustment, 0% PWM
B A
P
O
O
OO P
Figure 5 - Oil Control Valve Principle
Author: Seetareddy Beeravalli Version: V1.0 Page 5
CONCEPT OF MID-LOCK:
With the current VVT system, default position is at one end of cam phasing range. The cam can move in only one direction. There are some specific areas where there is further scope in improving fuel efficiency and cold start emission. This is achieved by introducing mid-lock in the VVT where in the default position is moved to an intermediate position. To start the VVT actuator from intermediate position a new lock is introduced which is controlled by digital actuator to lock or unlock with additional pin on ECU.
Along with this new requirement, the concept should also support existing VVT system. The current solution is upgraded to meet the new requirement wherein the actuator to move in both directions. This needed a complete function update of VVT from the base function models.
The algorithm was updated for new VVT actuator along with the test vectors.
Author: Seetareddy Beeravalli Version: V1.0 Page 6
Figure 6 – Adjustment range relative to default position for intlet side
Author: Seetareddy Beeravalli Version: V1.0 Page 7
PITFALL IDENTIFIED IN THE DESIGN BY MVS:
One of the requirements of the algorithm was to Cam phase Set point ( Desired value ) limitation. During the design, the strategy implemented did not work for the negative cam phasing. This was detected by simulating the model using test vectors. The deviation from expected value is observed as shown below.
The design is corrected and rechecked for the function behavior (picture below).
STIMULI
-10
0
10 CAM SP_PREL
setpoint/Signal Builder : Group 1
0 1 2 3 4 5 6 7 8 9 10
-20
-10
0
10
20 CAM_SP_LIM
Time (sec) Figure 7 – Input stimuli for model (signal A and B)
MODEL
Figure 8 – Design of logic before and after detecting design deviation
Author: Seetareddy Beeravalli Version: V1.0 Page 8
RESULT
Figure 9 - Verification with MVS
AUTO CODE GENERATION:
The model is converted to fixed point in which scaling is done for the signals and their operations. Scaling is the technique used to represent floating point signals in double precision with implementation variables using single precision float or integer resolution. To cross check whether scaling is correct, the fixed point model is simulated using the same test vectors. The deviation of the result from FLP (Floating Point) simulation result is observed (refer figure 11).
The verified FXP models were used for code generation using Embedded Coder© in Matlab environment.
The code was tested against the same test vectors used for validating the SDA model by using SIL/ PIL (refer figure 10) and confirmed with minimal effort that the software is working as expected and also confirmed that it will work on target platform (refer figure 11). The generated auto-code has been integrated in the Engine management Software (EMS) and tested on vehicle.
Author: Seetareddy Beeravalli Version: V1.0 Page 9
Figure 10 - MBD flow chart with SDA
Adhering to above steps of MBD results in a defect free code.
Figure 11 - Result from FLP, FXP, SIL, and PIL are identical
Author: Seetareddy Beeravalli Version: V1.0 Page 10
ALGORITHM OPTIMIZATION BASED ON SIL COVERAGE REPORT:
Based on SIL coverage report where dead codes are found due to design or scaling, are removed from the model. This is helpful even to test robustness of solution and even to save memory.
Dead
Code
LV_CAM_LOCK+
+
V.7.5
SET
RST
Q_in
Q
RST_DOMINANT
V.6.11
OR
V.6.6
NOT
V.6.6
V.6.5
V.6.5
V.6.5C_CAM_LOCK_HYS_VCP
V.6.4
C_CAM_LOCK_AMP_VCP
V.6.4
C_CAM_LOCK_BOL_VCP
V.6.4
C_CAM_LOCK_TOL_VCP
V.6.4
<CAM_PHA>
<CAM_PHA>
AND
V.6.9
<LV_CAM_LOCK>
<CAM_PHA>
LV_CAM_LOCK
Figure 12: Detection of dead code during MBD
0
20
40
60
80
100
Events
Co
vera
ge i
n %
Coverage report of decisions
Time sync tasks
Async tasks
Figure13: Coverage report for decisions
EFFORT COMPARISON:
To develop and validate the above solution for the new concept by manual coding was estimated to take 3 months. With MBD approach, the effort consumed for this algorithm development was 2 months, with added benefit of verified code against same test vectors.
Author: Seetareddy Beeravalli Version: V1.0 Page 11
0
50
100
150
200
250E
ffo
rt in
hr
Effort comparison
Manual Coding
MBD
Figure 14 – Comparison of effort between manual coding and MBD
CONCLUSION
The model based development approach is very useful to find pitfalls in solution at an early stage of development, and reduce probability of any software defect by detecting early using SIL/PIL. With above development, concept solution is validated and the time to develop is faster because lot of effort can be saved in development and testing of feedback control algorithms.
ACKNOWLEDGMENTS
I thank Continental for assigning the responsibility work on complex functions.
REFERENCES
1. Modern Control Engineering book written by Katsuhiko Ogata
2. Model based development environment at SiemensVDO Automotive AG, Division Powertrain, IAC2004 (Kunze, M.;
Reuther, A.)
3. Verification by Simulation within the model based development process at Continental Automotive Group, Business
Unit Engine Systems; Simulation and Test 2010 (Burger, T.; Kunze, M.; Schmidt, S.; Neiva Camargo, I.; Müller, R.)
CONTACT
Mr. Seetareddy Beeravalli
Powertrain Engine Systems,
Continental Automotive Components (India) Pvt. Ltd,
Author: Seetareddy Beeravalli Version: V1.0 Page 12
Technical Center, Ozone Manay Tech Park, 4th Floor, 56/18 and 55/9,
Garvebhavi palya, Hosur main Road,
Bangalore - 560068
Karnataka, India
Email: [email protected]
ADDITIONAL SOURCES
DEFINITIONS, ACRONYMS, ABBREVIATIONS
ACG: Auto Code Generation
EMS: Engine Management System
FLP: Floating point model
FXP: Fixed point model.
MIL: Model In Loop
SIL: Software In Loop
PIL: Processor In Loop
VVT: Variable Valve Timing
MBD: Model Based Development
SDA: System Design Automation