Patent Application
20140277994
1. Technical Field
The technical field relates to thermal management on internal combustion engines
2. Description of the Technical Field
Exhaust gas recirculation (EGR) sub-systems on internal combustion engines, particularly diesel engines, are employed, among other reasons, to control cylinder temperature. Limiting cylinder temperature reduces the generation of NOx. Control over the quantity of exhaust gas recirculated from the exhaust manifold to the intake manifold of an engine is implemented using an EGR valve. The temperature of the exhaust gas in the exhaust manifold can be managed using thermal management (TM) valve usually located ahead of exhaust treatment sub-systems such as catalytic converters and diesel particulate traps. A TM valve is used to increase backpressure in an exhaust system which raises exhaust gas temperature.
Achieving close thermal control over engine operation may be comprised by valve positioning response times. When EGR valves and TM valves exhibit slow or unpredictable responses the ability to achieve emission targets can be compromised.
Sliding mode control (SMC) is a nonlinear method of control that affects the dynamics of a system by use of a discontinuous control signal. This results in the system “sliding” along a cross-section of the system's usual response area. By way of example, sliding mode control may represent simple hard switching between two states, such as off to on. Asymptotic convergence on a state is avoided and system sensitivity of variations in variable values during a transition are avoided. A system thus may be made more robust. Implementing sliding mode control involves selection of a manifold (a “sliding surface”) such that the system performance trajectory exhibits closer to target behavior and finding a feedback gain that keeps the performance trajectory on the sliding surface.
In SMC the response of a closed loop system is defined by the parameters in the controller and is independent of both changes in the controlled system and disturbances acting on it. The technique has found prior application to proportional solenoid valves. Such valves have a natural third order, non-linear response which varies from valve to valve. Fluid flow through such valves can produce forces which oppose movement of the valve resulting in difficulties in obtaining target responses using conventional control methods.
A sliding mode controller for one or more valves in an engine induction or exhaust system provides improved thermal control over an engine. Double discrete variable rate filters generate position and velocity profiles for various intake and exhaust valves. Alternatively, double discrete fixed rate filters may be used to generate position and velocity profiles. A control law includes a Signum function and is modified with a “boundary layer” to control valve chattering. Alternatively, gain scheduling may be used to remove valve chattering. A low pass filter on the controller output can be used to remove chattering phenomena.
The sliding mode controller algorithm has calibratable position and velocity profile generator. This helps achieve variable rise times per requirements. Double butterworth filters are used for generating fixed rate profiles. Double first order filters are used to generate variable rate profiles. The gains on the filters can changed to achieve desired position and velocity profiles. The Signum function part of the control law is modified to incorporate a boundary layer which reduces the chattering phenomena. Gain scheduling algorithm is used to reduce chattering. When the error is greater than a threshold, one set of gains with a higher magnitude is used. When less than a threshold, lower magnitude gains are used. A low pass filter is implemented on the controller output to remove chattering, and humming sound from the motor at the end stops.
In the following detailed description, like reference numerals and characters may be used to designate identical, corresponding, or similar components in differing drawing figures. Furthermore, example sizes/models/values/ranges may be given with respect to specific embodiments but are not to be considered generally limiting.
Referring now to the drawings,
The induction and exhaust systems also include an intake air compressing (turbo-charger) sub-system 40. The intake air compressing sub-system 40 comprises a fixed geometry exhaust turbines (FGT) 41 and an air compressor 39 which is driven by the FGT 41. The intake air compressing sub-system 40 extracts energy from the exhaust stream in order to compress air (boost) for delivery to the combustion chambers 13. The intake air compressing sub-system 40 can be constructed from superchargers in which case there will be no exhaust turbines and the sub-system becomes exclusively part of the induction system. A waste gate 28 on the FGT 41 allows control over the amount of energy extracted from the exhaust stream in order to vary the boost to the combustion chambers 13.
The compressor 39 draws intake air at near ambient pressure and temperature and compresses the air for delivery to the intake manifold 50 through an (inter)cooler 42. Delivering air at greater than ambient pressure to combustion chambers 13 increases the air mass in the combustion chambers over a naturally aspirated engine and thereby allows more fuel to be injected. Increased amounts of energy are released with each combustion cycle resulting in the increased output of mechanical power. Thermodynamic law predicts that the extraction of energy from the exhaust stream will reduce the temperature of the exhaust stream moving downstream from the exhaust manifold 60 to discharge from the FGT 41. A portion of the exhaust gas stream is forced from the exhaust manifold 60 through the EGR valve 32 (when open) to the intake manifold 50 since the pressure in the exhaust manifold is higher than the pressure in the intake manifold.
Various sensors may be installed on the IC engine 10 or associated with the various sub-systems to monitor physical variables and generate signals which may be correlated to engine 10 operation and ambient conditions. The sensors include an ambient air pressure sensor 12, an ambient or intake air temperature sensor 14, and an intake air mass flow sensor 16, all which can be configured individually or as a single integrated device. In addition there are an intake manifold air temperature sensor 18, and an intake manifold pressure sensor 20. Additional sensors may include an FGT waste gate duty cycle sensor (not shown) and an EGR valve position sensor 30. A tachometer 22 monitors rotational speed in revolutions per minute (N) of the crankshaft 23. Engine speed (N) may be derived from a cam shaft position sensor (not shown) in the absence of a crankshaft associated tachometer 22. An exhaust manifold temperature sensor 31 and an exhaust manifold pressure sensor 17 may be located in physical communication with the exhaust manifold 60. A post fixed geometry turbine pressure sensor 26 measures pressure of the exhaust gas upon discharge from the low pressure FGT 41 and the thermal management valve 80. A pressure difference sensor 27 measures pressure drop across the DPF 68. A temperature sensor 19 provides exhaust gas temperature after discharge from the PRE-DOC filter 75. The present disclosure outlines methods for the estimation of gas temperature in the exhaust manifold based on particular sets of sensors to supplement or replace exhaust manifold temperature sensor 31. The enumeration of the various sensors does not mean all are present on every vehicle or that others might not be present. Data links of various types (not shown) may be used to connect sensor readings to the ECM 25. The intake and exhaust sub-system configurations are exemplary and the present teachings can be applied to other arrangements of sub-system elements.
ECM 25 receives engine oil and engine coolant temperature measurements from IC engine 10 sensors (not shown). Torque demand 21 is a function of driver pedal position. Engine speed (N) and torque demand 21 are used to determine torque (R). Friction losses depend upon engine speed (N).
The readings from the sensors, where present, represent several operating variables, including: Tim—intake manifold temperature from sensor 18; Pim—intake manifold pressure from sensor 20; Tam—ambient temperature from intake air temperature sensor 14; Pam—ambient pressure from ambient air pressure sensor 12; WGTP—high pressure FGT 41a waste gate 29 position from waste gate duty cycle sensor 28; EGVp—EGR valve 32 position from sensor 30; N—engine speed from tachometer 22; Pem—exhaust manifold pressure from exhaust manifold pressure sensor 17; Pat—exhaust pressure upon discharge from LP FGT 41b from post LP FGT pressure sensor 26; Ppc—pressure change across the DPF 68 from DPF pressure difference sensor 27, this value may be used to determine pressure at the outlet from the LP FGT 41b assuming pressure drop across the PRE-DOC 75 and DOC 70 are negligible; and, Tpc—exhaust gas temperature after discharge from the PRE-DOC 75 comes from a temperature sensor 19. An exhaust manifold temperature sensor 31 generating a measured value Tem for exhaust gas temperature in the exhaust manifold 60.
Referring to
Profile generator 202 is now considered in greater detail referring to
Where n is the order of the filter, and wn is the cutoff frequency. For our design, the following are chosen,
A double variable rate discrete first order filter is used for the generation of the target position and velocities. A variable rate filter is used instead of a fixed rate filter to obtain proportional rise times for the given step changes. The following logic is applied where filter time constant (tc) is varied dynamically based on the delta step changes.
Pos_out(i)=Pos_in(i)*(ts/(ts+tc))+Pos_out(i−1)*(tc/(tc+ts) (1)
Pos_in is the delta step change requested. There is a linear gain which modifies the time constant (tc) based on the magnitude of the Pos_in. A discrete derivative is used to obtain the target velocity from the target position.
2=f(x1,x2)+bU (2)
f(x1,x2)=Ks(x1)*x1+Kf(x2)*x2
Ks is the spring constant
Kf is the damping constant
U is the Control signal between −60000, 60000 where 60,000 and −60,000 are the maximum torque outputs in positive and negative directions and “b” is the transfer function from U to Electro-Mechanical Torque.
Referring to
S=e+Kp Kp>0 (3)
e is the tracking error which is the difference between the target position and actual position and is the tracking error, is the difference between the desired velocity and actual velocity.
Assuming a control law such that
S≦−ρ|S| ρ>0 (4)
then the sliding surface (s=0) is reached within a finite time, given by S(t—0)/ρ, where t—0 is the initial time.
The functions f(x) and b are not known exactly but their nominal values are known in terms of the nominal values of plant parameters and current states. Let these be donated by {tilde over (ƒ)}(x) and {tilde over (b)}. Assuming that f(x) and b satisfying the below inequalities,
|ƒ−{tilde over (ƒ)}|≦F (5)
b_min≦b≦b_max (6)
then control law ensures the satisfaction of inequality 3 and helps drive the system to the sliding surface (S=0) within a finite time and
U=Ũ−Ki Sgn(S) (7)
Where Ũ=(1/{tilde over (b)})(2des−f(x)−Kp·x2des)
Sgn is the sign function. It is +1 when S>=0 and −1 when S<0
However, because of Sgn(S), the input U to the plant chatters. This is the major drawback of the classical sliding control design as chatter might trigger unmodeled high frequency dynamics in the system. Also, the high control activity should be avoided which is not practical to implement. The control law should provide durability to the system which might not be possible with high switching frequencies reducing the life of the electronics board, and as well as affecting the mechanical part of the valve with the unwanted vibrations.
One way to smooth the control signal is to replace Sgn(S) with a saturation function sat(S/φ). Here φ is the boundary layer thickness around S=0 where the saturation function is linear in S/φ. For simplicity and practical implementation, the signum component of the control law is replaced as follows,
U_Signum=Kd·S,−Ki≦Kd·S≦+Ki (8)
This assures that when S is large the U component is large enough to drive the surface to zero and when S is small, this component becomes very small and helps minimizes the chattering effect. Ki above is assumed to be largest U possible(ex. 60,000 (maximum effort) in positive direction and −60,000 (maximum effort) in negative direction). The control law (7) can then be modified to
U=Ũ−Kd·S,−Ki≦Kd·S≦+Ki (9)
Though the sliding control design 1 helps to minimize the chattering effect However the design does not guarantee that we would reach sliding surface (S=0) in finite time in all the conditions.
Referring to
S=+(2·Kp)e+Kp2∫e dt from t0 to t (10)
The integrator term on the tracking error term of position will always ensure that the tracking error on the position will always converge towards 0. Now the control law (9) is modified as
U=Ũ−Kd·S,−Ki≦Kd·S≦+Ki
S is given by equation (8)
Ũ=(1/{tilde over (b)})(2des−{tilde over (f)}(x)−2·Kp×e−Kp2e) (11)
Based on experimental evaluation of design 1, it was noted that the nominal values {tilde over (f)}(x) contributed to a large steady state error for small steady changes. This could be attributed to not a very accurate calibration of the plant model at small step changes. And hence, it seemed reasonable to move ahead with design of putting together an integral control in SMC assuming no nominal spring and damping forces in equation (11).
Ũ=(1/{tilde over (b)})(2des−2·Kp×e−Kp2e) (12)
Referring to
Refereeing to
(x2)=y+L*(x1−x1) (13)
Where the auxiliary variable is updated according to the following
=(1/J)*(−f(x1,x2)+b*U) (14)
L is the observer gain which is adapted by performing experiments on the bench top. The function f(x1, x2) is the characterization (spring forces, damping forces), and J is the inertia of the plant model. This is a combination of spring and damping constant lookup tables for the plant model.
Referring to
Referring to
Referring to
Referring to
Referring to
Referring to
Referring to
Referring to
Referring to
Referring to
Referring to
The results of
Primary gains (when error on position is greater than 2 degrees)
Secondary gains (when error on position is less than 2 degrees)
Referring to
The controllers developed (SMC Fixed rate, SMC Fixed rate with integral control, and SMC variable rate with integral control) for the given hardware helps to achieve faster valve performance, remove steady state errors and remove erratic behavior. The controller law whether linear or non-linear should take account of the hardware variability's, instabilities and external noise factors to produce required performance attributes. SMC defines a sliding surface (S) which is first order function of error on displacement and velocity. The controller law guarantees reaching the sliding surface (s=0) notwithstanding external disturbances such as flow forces, or hardware uncertainties. The control law has a profile generator, surface calculation, velocity observer, and a first order filter on the controller output. The fixed rate filter is used to provide same position and velocity profiles irrespective of the step changes. Whereas variable rate filter provides proportional position and velocity profiles depending on delta step changes.
The system provides valve step response (5-95) below 125 ms, starts valve movement below 10 ms when commanded, provides stable valve control, provides faster response valves means faster reaction to requested egr flows for lower NOx, reduces chattering which is common to classic SMC, provides for stable valve positioning for onboard diagnostic development, the controller could be quickly adapted to different valves like EGR, TM, intake throttle etc., and finally the controller could be quickly adapted per requirements like rise time etc.
