Abstract:
A method for simultaneously measuring one or more properties (e.g. temperature, concentration of NO x  and ammonia, etc) in an exhaust gas mixture. Signals from one or more sensors that are cross-sensitive to one or more gases can be combined. A decoupling observer algorithm can be applied, such that these cross-sensitivities are decoupled. The sensors simultaneously obtain an estimate of one or more gases in the diesel exhaust. A decoupling observer algorithm can be structured and arranged to be operable among a plurality of positions corresponding to several internal configurations.

Description:
TECHNICAL FIELD 
     Embodiments are generally related to sensor methods and systems. Embodiments are also related to diesel exhaust after-treatment devices. Embodiments are additionally related to techniques and devices for simultaneously measuring one or more properties associated with diesel exhaust. 
     BACKGROUND OF THE INVENTION 
     Environmental pollution, such as air pollution, is a serious problem that is particularly acute in urban areas. Much of this pollution is produced by exhaust emissions from motor vehicles. NO x  gases, which are present in automotive exhaust pollution, are known to cause various environmental problems such as smog and acid rain. The term NO x  actually refers to several forms of nitrogen oxides such as NO (nitric oxide) and NO 2  (nitrogen dioxide). Nitrogen oxide (NO x ) contained in exhaust gas can directly effect the human body. NO x  and its emission concentrations in various exhaust gases also contribute to the formation of “acid rain” and photochemical smog. Hence, it is necessary to remove NO x  from exhaust gas. 
     Selective Catalytic Reduction (SCR) is a technique that is used to inject urea—often a liquid-reductant agent—into an exhaust stream of a diesel engine, which is then adsorbed onto the surface of a catalytic converter. In an SCR system, urea is used as a reductant that is converted to ammonia which reacts in the presence of a catalyst to convert NO x  to nitrogen and water which is then expelled through a vehicle tailpipe. Precise ammonia and NOx measurements are required to develop and characterize optimal catalyst strategies in order to prevent excess ammonia emissions or un-reacted NO x  emissions. Note that the term “ammonia slip” refers to excessive ammonia emission which in practice may be caused by exhaust gas temperatures that are too cold for the SCR reaction to occur (such as during a cold start), or if the urea injection device feeds too much reductant into the exhaust gas stream for the amount of NO x  produced by the engine combustion. 
     A technology that can immediately control the NH 3  feed rate according to the load change, fluctuation in NO x  concentration, and so forth, is therefore needed in order to realize high-efficiency NO x  removal without leaving un-reacted NH 3 . A measuring technology with a high-speed response capable of simultaneous and continuous measurement of NO x  and NH 3  would be indispensable. Sensors designed for NO x  or NH 3 , however, are often significantly cross-sensitive to each other. Distinguishing these components is therefore critical to successfully controlling an SCR device. It is believed that the control of SCR devices would benefit from the simultaneous measurements of NO x  and NH 3 . 
     One approach for the development of simultaneous NO x /NH 3  sensor in exhaust gas involves the use of two identical sensors for measuring NO x  and NH 3  by splitting the exhaust path in two and running each path through a different catalyst prior to entry into the respective sensor. This technique is suitable for stationary power plant application but is very expensive to implement and takes up a great deal of space and is thus not suitable for automotive applications. 
     In an effort to address the foregoing difficulties, it is believed that two sensors with dissimilar sensitivities and cross sensitivities to NO x  and NH 3  can be combined and a decoupling observer algorithm applied for simultaneously measuring NO x  and NH 3  in diesel exhaust as described in greater detail herein. 
     BRIEF SUMMARY 
     The following summary is provided to facilitate an understanding of some of the innovative features unique to the embodiments disclosed and is not intended to be a full description. A full appreciation of the various aspects of the embodiments can be gained by taking the entire specification, claims, drawings, and abstract as a whole. 
     It is, therefore, one aspect of the present invention to provide for an improved sensor method and system. 
     It is another aspect of the present invention to provide for improved diesel exhaust after treatment devices. 
     It is a further aspect of the present invention to provide for a method and system for simultaneously measure one or more properties (e.g., concentrations NO x  and ammonia, temperature, etc) associated with an exhaust gas mixture. 
     The aforementioned aspects and other objectives and advantages can now be achieved as described herein. A method and system for simultaneously measuring a plurality of properties (e.g., gas, temperatures, etc.) of an exhaust gas mixture (e.g., diesel exhaust) is disclosed. Signals from a plurality of sensors that are cross-sensitive to a first property (e.g., NO x ) and a second property (e.g., NH 3 ) can be combined. A decoupling observer algorithm can be applied, such that these cross-sensitivities are decoupled and the sensors simultaneously obtain an estimate of one or more such properties. Such a method and system can enable the use of inexpensive sensor technologies that have been previously ruled out due to their cross-sensitivities. Possible configurations utilizing such sensors and a decoupling observer algorithm can include, for example, control module (ECM) based configurations, intelligent sensor configurations, and/or intelligent sensor configuration for on board diagnostics. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The accompanying figures, in which like reference numerals refer to identical or functionally-similar elements throughout the separate views and which are incorporated in and form a part of the specification, further illustrate the embodiments and, together with the detailed description, serve to explain the embodiments disclosed herein. 
         FIG. 1  illustrates a block diagram of an example data-processing apparatus, which can be adapted for use in implementing a preferred embodiment; 
         FIG. 2  illustrates a schematic diagram of a closed-loop SCR control system  200  based on ECM configuration for simultaneously measuring NO x  and NH 3 , in accordance with a preferred embodiment; 
         FIG. 3  illustrates a schematic diagram of a closed-loop SCR control system based on intelligent sensor configuration for simultaneously measuring NO x  and NH 3 , which can be implemented in accordance with an alternative embodiment; 
         FIG. 4  illustrates a schematic diagram of a closed-loop SCR control system based on intelligent sensor configuration for on-board diagnostics (OBD) for simultaneously measuring NO x  and NH 3 , which can be implemented in accordance with an alternative embodiment; and 
         FIG. 5  illustrates a high level flow chart of operations illustrating logical operational steps of a method for simultaneous measurement of NO x  and ammonia in diesel exhaust, in accordance with an alternative embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     The particular values and configurations discussed in these non-limiting examples can be varied and are cited merely to illustrate at least one embodiment and are not intended to limit the scope thereof. 
       FIG. 1  illustrates a block diagram of a data-processing apparatus  100 , which can be adapted for use in implementing a preferred embodiment. It can be appreciated that data-processing apparatus  100  represents merely one example of a device or system that can be utilized to implement the methods and systems described herein. Other types of data-processing systems can also be utilized to implement the present invention. Data-processing apparatus  100  can be configured to include a general purpose computing device  102 . The computing device  102  generally includes a processing unit  104 , a memory  106 , and a system bus  108  that operatively couples the various system components to the processing unit  104 . One or more processing units  104  operate as either a single central processing unit (CPU) or a parallel processing environment. A user input device  129  such as a mouse and/or keyboard can also be connected to system bus  108 . 
     The data-processing apparatus  100  further includes one or more data storage devices for storing and reading program and other data. Examples of such data storage devices include a hard disk drive  110  for reading from and writing to a hard disk (not shown), a magnetic disk drive  112  for reading from or writing to a removable magnetic disk (not shown), and an optical disc drive  114  for reading from or writing to a removable optical disc (not shown), such as a CD-ROM or other optical medium. A monitor  122  is connected to the system bus  108  through an adapter  124  or other interface. Additionally, the data-processing apparatus  100  can include other peripheral output devices (not shown), such as speakers and printers. 
     The hard disk drive  110 , magnetic disk drive  112 , and optical disc drive  114  are connected to the system bus  108  by a hard disk drive interface  116 , a magnetic disk drive interface  118 , and an optical disc drive interface  120 , respectively. These drives and their associated computer-readable media provide nonvolatile storage of computer-readable instructions, data structures, program modules, and other data for use by the data-processing apparatus  100 . Note that such computer-readable instructions, data structures, program modules, and other data can be implemented as a module  107 . Module  107  can be utilized to implement the methods  300 ,  400  and  500  depicted and described herein with respect to  FIGS. 3 ,  4  and  5 . Module  107  and data-processing apparatus  100  can therefore be utilized in combination with one another to perform a variety of instructional steps, operations and methods, such as the methods described in greater detail herein. 
     Note that the embodiments disclosed herein can be implemented in the context of a host operating system and one or more module(s)  107 . In the computer programming arts, a software module can be typically implemented as a collection of routines and/or data structures that perform particular tasks or implement a particular abstract data type. 
     Software modules generally comprise instruction media storable within a memory location of a data-processing apparatus and are typically composed of two parts. First, a software module may list the constants, data types, variable, routines and the like that can be accessed by other modules or routines. Second, a software module can be configured as an implementation, which can be private (i.e., accessible perhaps only to the module), and that contains the source code that actually implements the routines or subroutines upon which the module is based. The term module, as utilized herein can therefore refer to software modules or implementations thereof. Such modules can be utilized separately or together to form a program product that can be implemented through signal-bearing media, including transmission media and recordable media. 
     It is important to note that, although the embodiments are described in the context of a fully functional data-processing apparatus such as data-processing apparatus  100 , those skilled in the art will appreciate that the mechanisms of the present invention are capable of being distributed as a program product in a variety of forms, and that the present invention applies equally regardless of the particular type of signal-bearing media utilized to actually carry out the distribution. Examples of signal bearing media include, but are not limited to, recordable-type media such as floppy disks or CD ROMs and transmission-type media such as analogue or digital communications links. 
     Any type of computer-readable media that can store data that is accessible by a computer, such as magnetic cassettes, flash memory cards, digital versatile discs (DVDs), Bernoulli cartridges, random access memories (RAMs), and read only memories (ROMs) can be used in connection with the embodiments. 
     A number of program modules, such as, for example, module  107 , can be stored or encoded in a machine readable medium such as the hard disk drive  110 , the magnetic disk drive  112 , the optical disc drive  114 , ROM, RAM, etc or an electrical signal such as an electronic data stream received through a communications channel. These program modules can include an operating system, one or more application programs, other program modules, and program data. 
     The data-processing apparatus  100  can operate in a networked environment using logical connections to one or more remote computers (not shown). These logical connections can be implemented using a communication device coupled to or integral with the data-processing apparatus  100 . The data sequence to be analyzed can reside on a remote computer in the networked environment. The remote computer can be another computer, a server, a router, a network PC, a client, or a peer device or other common network node.  FIG. 1  depicts the logical connection as a network connection  126  interfacing with the data-processing apparatus  100  through a network interface  128 . Such networking environments are commonplace in office networks, enterprise-wide computer networks, intranets, and the Internet, which are all types of networks. It will be appreciated by those skilled in the art that the network connections shown are provided by way of example and that other means and communications devices for establishing a communications link between the computers can be used. 
       FIG. 2  illustrates a schematic diagram of a closed-loop SCR control system  200  based on ECM configuration for simultaneously measuring NO x  and NH 3 , in accordance with a preferred embodiment. An SCR control algorithm may require simultaneous estimates of both NOx and NH 3  emissions levels in order to determine the level of urea dosing that is appropriate for the urea dosing unit. Such an algorithm can be provided in a software module, such as, for example, module  107  depicted in  FIG. 1 , and processed via a processing device or microprocessor, such as the processor  104  also depicted in  FIG. 1 . 
     The SCR control algorithm  210  as shown in  FIG. 2  can be configured to collect information from various sensors operating within system  100  and the host system and to provide control signals that affect the operations of system  100  and/or the host system. SCR control algorithm  210  can be a module  107  programmed or hardwired within an ECM (Electronic control module)  215  as shown in  FIG. 2  in order to perform operations dedicated to certain functions. The SCR control algorithm  210  can thus be provided as software that is stored as instructions and/or data within a memory device  106  of an ECM  215  for execution by a processor  104  operating within the ECM  215 . Alternatively, SCR control algorithm  210  can be a module  107  that is separate from other components of a host system. 
     As illustrated in  FIG. 2 , the system  200  can include a urea dosing unit  225 , a urea injector  235 , the SCR control algorithm  210 , an exhaust system  240 , and an SCR catalyst component  230 . Arrow  241  indicates the flow of exhaust and/or other gases from the exhaust system  240  to the urea injector  235 , which is connected to and forms a part of the SCR catalyst component  230 . Urea injector  235  can be provided as a device that is hardware and/or software controlled and which extracts the urea solution from the urea dosing unit  225 . The SCR catalyst component  230  can allow the NO x  molecules within the exhaust gas engine  240  out to react with ammonia molecules to produce molecular nitrogen (N 2 ) and water (H 2 O). Further, system  200  can include physical sensors  245  and  250  that can be configured to measure and/or analyze NO x  emissions exhausted from the exhaust system  240  after the use of the SCR catalyst component  230 . 
     The sensors  245  and  250  can also provide actual NO x  emission values to SCR control algorithm  210  based on the use of decoupling observer algorithm  220  associated with system  200 . Note that algorithm  220  can also be provided as a software module, such as, for example, module  107  of  FIG. 1 . The data-processing apparatus  100  together with the SCR control algorithm  210  can therefore be utilized to monitor and control the operations associated with SCR system  200 . According to one embodiment of the present invention, SCR control algorithm  210  can be implemented as a part of an Engine Control Module (ECM)  215  that monitors and controls the operation of an engine associated with system  200 . 
     The SCR control system  200  can inject a source of NH 3  usually urea  235  from a urea dosing unit  225  into the exhaust gas engine output path  240 . The dosing of urea solution into the urea injector  235  can be precisely controlled by the urea dosing unit  225 . The NH 3  is then adsorbed on to the surface of the SCR catalyst  230  and reacts with the exhaust NO x  from the exhaust gas engine output path  240  to form harmless N 2  and H 2 O emissions, which pass through and out the exhaust gas tailpipe  254  as indicated by arrow  255 . The true concentration of NO x  and NH 3  from the exhaust gas is shown as w 1  and w 2  in  FIG. 2 . Poor NH 3  mixing, temperature-dependant catalyst efficiencies, catalyst aging, rapidly changing engine-out exhaust gas  240  properties and so forth are factors that can contribute to non-ideal chemical reactions and thus elevated NO x  or NH 3  tailpipe emissions as indicated by arrow  255 . It can be appreciated that although the embodiments discussed herein relate to the simultaneous measurement of NO x  and NH 3  in diesel exhaust, the embodiments can apply to measuring other types of gases. NO x  and NH 3  are therefore presented herein for general illustrative purposes. Other types of gases can also be measured according to the general methodology and configuration discussed herein. 
     In the ECM configuration of system  200 , the decoupling observer algorithm  220  can be located onboard the ECM  215 . The DOA  220  receives signals y 1  and y 2  as illustrated in  FIG. 2  from the sensors  245  and  250  and converts such signals into estimates of NO x  and NH 3  as respectively shown as z 1  and z 2  in  FIG. 2 . The SCR controller algorithm  210  then uses the estimated NO x  and NH 3  values z 1  and z 2  to command an appropriate amount of urea u as shown through urea dosing unit  225  into urea injector  235  such that tailpipe-out emissions as indicated by arrow  255  satisfy NO x  and NH 3  emissions targets. 
     The signal processing design for NO x  can be represented as follows. The response of the first sensor  245  can be modeled by the dynamical relationship as indicated by equation (1) below:
 
 y   1 ( t )= g   11 ( s ) w   1 ( t )+ g   12 ( s ) w   2 ( t )  (1)
 
     where g 11  represents the response of sensor  245  to NO x  and g 12  represents the response of sensor  245  to NH 3 . Where the notation x(t) represents a signal as a function of time t. In this context, the notation g(s) refers to a transfer function defined as follows
         Let the signal x(t) be the input to a general linear time-invariant system, and let the signal y(t) be the output, and the Laplace transform of x(t) and y(t) be respectively       

     
       
         
           
             
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     First to highlight the benefits of the inventive two-sensor and signal processing technique, we present a brief overview of the issues involved in attempting to measure NOx using only a single sensor with a typical response as shown in equation (1). Since only a single sensor is available, then we can write the signal processing logic as the scalar function as indicated by equation (2) below:
 
 z   1 ( t )= h   11 ( s ) y   1 ( t )  (2)
 
     where h 11 (s) represents a signal processing filter. Then assuming that we want to obtain an estimate of the NO x  in the tailpipe, we will require that z 1 ≈w 1  over the frequency range of interest. Then combining the signal processing algorithm in equation (2) with the sensor response equation (1), we find that satisfying z 1 =w 1  requires h 11 (jω)=g 11 (jω) −1  and g 12 (jω)=0. The requirement of h 11 (jω)=g 11 (jω) −1  is a straightforward signal processing design requirement. But on the other hand, the requirement that g 12 (jω)=0 means that one must impose the very demanding requirement of zero-cross-sensitivity on the sensor hardware itself. Constructing a sensor with negligible cross-sensitivities is well-known to be more challenging and expensive than permitting some cross-sensitivities. 
     With this in mind, now consider the inventive technique of adding a second sensor of dissimilar sensitivities to NO x  and NH 3 . Analogous to the discussion on NO x  sensing, the second sensor  250  response can be provided as given by a similar linear dynamical relationship as indicated by equation (3) below:
 
 y   2 ( t )= g   21 ( s ) w   1 ( t )+ g   22 ( s ) w   2 ( t )  (3)
 
     where g 21  represents the frequency response of sensors  245  and  250  to NO x  and g 22  represents the response of sensors  245  and  250  to NH 3 . 
     The two sensor responses as shown in equation (1) and (3) can be combined into a single equation as follows: 
     
       
         
           
             
               
                 
                   
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     Next, consider designing a multivariable signal processing algorithm from the raw sensor signals measured as shown in equation (2) and (4): 
     
       
         
           
             
               
                 
                   
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     Then in order to design the 2-by-2 transfer matrix for a signal processing filter H(s) such that z 1 =w 1  and z 2 =w 2 , the sensors  245  and  250  response G(s) to NO x  and NH 3  need to be invertible in the frequency range of interest. (The frequency response of a stable transfer function such as (6) may be obtained by substituting s=jω where ω represents the frequency and j=√{square root over (−1)}.) This leads to a much milder requirement on the sensors  245  and  250  cross-sensitivities than for a single sensor. Using two sensors leads to the much easier condition can be applied as shown in equation (7) over the frequency range of interest.
 
 g   11 ( s ) g   22 ( s )≠ g   21 ( s ) g   12 ( s )  (7)
 
which represents a strict mathematical condition for the invertibility of the transfer matrix in G(s) in (5). A practical extension of the condition would necessarily require that the matrix be well-conditioned in addition to invertible. In other words, that the condition number of the interaction matrix G(s) in (5) (defined as the ratio between the maximum and minimum singular values) satisfies,
 
                     cond   ⁡     (     G   ⁡     (     j   ⁢           ⁢   ω     )       )       ≡         σ   _     ⁡     (     G   ⁡     (   jω   )       )           σ   _     ⁡     (     G   ⁡     (   jω   )       )         ⪡   ∞           (   8   )               
for all frequencies |ω|&lt;ω c . Where ω c  represents the highest frequency of interest.
 
     Which does not require zero cross-sensitivities in either of the two sensors, and can still produce estimates of both NO x  and NH 3 . Thus combining the information provided by two sensors of dissimilar sensitivities allows obtains more information than could have been obtained by separate analysis of both sensors in isolation. 
     From equation (7) it becomes mathematically possible to design H(s) as a decoupling observer algorithm by designing H(jω)≈G(jω) −1  in equation (6). For linear systems, there are many fairly standard techniques for design of decoupling observer algorithm H(s) with respect to the sensor characteristics G(s). The transfer matrix norm-based techniques for design of decoupling observer algorithm denoted by transfer matrix H(s) with respect to the sensor characteristics modeled by transfer matrix G(s) are depicted in equation (9) and (10). 
     
       
         
           
             
               
                 
                   
                     
                       
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     More complex techniques also exist for nonlinear systems. 
       FIG. 3  illustrates a schematic diagram of a closed-loop SCR control system  300  based on an intelligent sensor configuration for simultaneously measuring NO x  and NH 3  in accordance with an alternative embodiment. Note that in  FIGS. 1-4 , identical or similar parts or elements are generally indicated by identical reference numerals. Additionally, it can be appreciated that although properties such as NO x  and NH 3  can be measured according to the method and system disclosed herein, other properties such as the temperature of an exhaust gas mixture can also be measured, in addition concentrations of various gases associated with the exhaust gas mixture. The feature applies equally to all embodiments disclosed herein. 
     The intelligent sensor configuration of system  300  contains the same functional blocks as in the ECM configuration  200  as shown in  FIG. 2 . The difference between the configurations of  FIGS. 2 and 3  lies in the packaging arrangement. The intelligent sensor or system  300  produces NO x  and NH 3  estimates, which can potentially be used in the context of the third party SCR control algorithm  210  described above 
     Referring to  FIG. 4 , a schematic diagram of a closed-loop SCR control system  400  based on an intelligent sensor configuration for on board diagnostics (OBD)  410  for simultaneously measuring NO x  and NH 3 , is illustrated, in accordance with an alternative embodiment. Note that in  FIGS. 1-4 , identical or similar parts or elements are generally indicated by identical reference numerals. Tailpipe emissions indicated by arrow  255  can be monitored by the OBD unit  410  on a continual basis. NO x  level monitoring can also accomplish monitoring of the presence of urea in the system. 
     The OBD  410  can support actions such as warning the operator when urea tank (not shown) levels are low, which will trigger an enforcement action if the urea tank is empty or near empty. Additionally, a triggering warning and enforcement action may occur if fluid other than urea is filled into the urea tank and detected by a urea concentration or ammonia sensor. In such a situation, an alert can be provided warning the operator and/or triggering enforcement action if the NO x  levels exceed a particular threshold or limits. Enforcement actions of increasing severity can be triggered depending upon the duration of high NO x  levels. 
     It will be obvious to those skilled in the art that the method disclosed herein can be extended for use by combining N sensors, each with different sensitivities, to separately estimate the levels of N different chemical species. For example, consider N=3 in diesel exhaust, wherein three sensors of dissimilar sensitivities to NO, NO 2  and NH 3  are combined. In such a case, signal processing logic could be designed by the method described above to provide estimates of the amounts NO, NO 2 , and NH 3  species in the exhaust. There are many applications (including the operation of SCR aftertreatment devices) in which understanding NOx in terms of its constituent NO and NO 2  components would be valuable. 
     Referring to  FIG. 5 , a high-level flow chart of operations illustrating logical operational steps of a method  500  for the simultaneous measurement of NO x  and ammonia in diesel exhaust is illustrated, in accordance with a preferred embodiment. The sources of ammonia (e.g., usually urea) can be injected into an exhaust gas path  240 , as depicted at block  510 . Thereafter, as indicated at block  520 , ammonia can be adsorbed onto the catalytic surface  230 , which reacts with NO x  in order to form harmless N 2  and H 2 O. Two sensors  245  and  250  having dissimilar sensitivities and cross-sensitivities to NO x  and NH 3  can be combined, as shown at block  530 . Next, as described at block  540 , the cross-sensitivities of NO x  and NH 3  can be decoupled and measured using the previously described decoupling observer algorithm  220 . An appropriate amount of urea can be commanded using an SCR control algorithm  210 , as depicted at block  550 , which is then used to inject a source of ammonia into the exhaust gas path. 
     It can be appreciated that a variety of alternative embodiments can be implemented in accordance with the methods and systems described herein. For example, one alternative embodiment can utilize simultaneous NO x  and NH 3  measurements in the feedback control of an aftertreatment device with active ammonia dosing. SCR is the most common example of such aftertreatment devices. Such configurations and related methods thereof are preferably independent of the cross-sensitivities and decoupling algorithms discussed previously. Such a situation addresses the problem where for example, an NO x  sensor and an NH 3  sensor do not possess significant cross-sensitivities. 
     The overall concept disclosed herein is actually general in nature. The embodiments discussed herein have been described in the context of the two properties NO x  and NH 3 , but the disclosed invention can be extended to consider N sensors of dissimilar cross-sensitivities to N different physical properties in diesel exhaust. A few specific examples include: 
     With N=3 one can measure NO, NO 2  and NH 3 . An aftertreatment device can benefit from additional implementations regarding the partitioning of NO x  into its constituent NO and NO 2 . For example, the response and effectiveness of an SCR aftertreatment device is strongly dependant on the ratio of NO to NO 2  in the exhaust NO x . 
     With N=3 again, consider measuring NO x  and NH 3  and decoupling cross-sensitivity to Temperature. The decoupling of temperature sensitivity is a crucial issue in practically all sensor design problems. 
     It will be appreciated that variations of the above-disclosed and other features and functions, or alternatives thereof, may be desirably combined into many other different systems or applications. Also that various presently unforeseen or unanticipated alternatives, modifications, variations or improvements therein may be subsequently made by those skilled in the art which are also intended to be encompassed by the following claims.