Description:Complete Specification:
The following specification describes and ascertains the nature of this invention and the manner in which it is to be performed:

Field of the invention:
[0001] The present disclosure relates to a controller and method to estimate a quantity of Nitrogen Oxides (NOx) emission from an engine without using a dedicated sensor.

Background of the invention:
[0002] According to a prior art 2074/CHENP/2014 discloses a NOx model. Methods are provided for estimating the NOx content of exhaust gas produced by an internal combustion engine. The method includes determining one or more operating parameters. The method further includes applying the determined operating parameter(s) to a global NOx model. The global NOx model may be derived using a plurality of steady state data points relating to local NOx emission models. The steady state data points may be derived using a plurality of set and variable operating parameters. The global NOx model allows for prediction of the engine-out NOx content of exhaust gas in real time and without a NOx sensor, even if engine operating parameters change.

Brief description of the accompanying drawings:
[0003] An embodiment of the disclosure is described with reference to the following accompanying drawings,
[0004] Fig. 1 illustrates a block diagram of a controller to estimate a quantity of Nitrogen Oxides (NOx) emission from an engine without using a dedicated sensor, according to an embodiment of the present invention, and
[0005] Fig. 2 illustrates a flow diagram of a method for estimating the quantity of Nitrogen Oxides (NOx) emission from the engine without using the dedicated sensor, according to the present invention.

Detailed description of the embodiments:
[0006] Fig. 1 illustrates a block diagram of a controller to estimate a quantity of Nitrogen Oxides (NOx) emission from an engine without using a dedicated sensor, according to an embodiment of the present invention. The controller 110 configured to receive input signals for engine parameters. The engine parameters are either measured from respective sensors or estimated, characterized in that, the controller 110 calculates a quantity of fuel flow into at least one cylinder of the engine (not shown). The fuel quantity is either determined using the characteristics of injectors such as time of injection and duration of injection. Alternatively, at least one measured engine parameters are used to determine the fuel injection quantity. The controller 110 then determines a correction factor for each of the measured engine parameter, and estimates quantity of the NOx emission through a model by using correction factors and the calculated quantity of fuel flow. In the model, the controller 110 multiplies the determined correction factors with the calculated quantity of fuel flow (such as in grams/second). The controller 110 provides output 112 as the quantity of NOx emissions. The output 112 is used for taking corrective measures such as purging a catalyst.

[0007] According to an embodiment of the present invention, the quantity of fuel flow to the at least one cylinder is calculated using the engine map pre-stored in the controller 110. The quantity of fuel flow also depends upon the air flow, a manifold pressure and temperature, which are measured by respective sensors such as oxygen sensor or lambda sensor 106, a Manifold Air Pressure (MAP) sensor 102 and air temperature sensor 104 as per the relation Fuel flow = air flow / (14.7 * lambda). The relation is provided for understanding and may or may not be subject to corrections as per the actual implementation. Further, the fuel flow may be derived using the pressure of fuel at the injector and the opening time of the injector.

[0008] In accordance to an embodiment of the present invention, the engine parameters comprises engine-out lambda value, ignition timing, engine temperature, intake manifold pressure and exhaust temperature. The engine-out lambda value is measured by the oxygen sensor or lambda sensor 106, the ignition timing is controlled based on the engine speed sensor 108, the engine temperature is measured by engine temperature sensor (not shown) and the intake manifold pressure is measured by the MAP sensor 102 and the exhaust temperature is measured by the exhaust temperature sensor (not shown).

[0009] In accordance to an embodiment of the present invention, the controller 110 is provided with necessary signal detection, acquisition, and processing circuits. The controller 110 is the control unit which comprises input/output interfaces having pins or ports, a memory element 114 such as Random Access Memory (RAM) and/or Read Only Memory (ROM), Analog-to-Digital Converter (ADC) and a Digital-to-Analog Convertor (DAC), clocks, timers, counters and at least one processor (capable of implementing machine learning) connected with each other and to other components through communication bus channels. The memory element 114 is pre-stored with logics or instructions or programs or applications or modules/models and/or threshold/safe limit values/ranges, predefined/predetermined criteria, correction factor based maps/table which is/are accessed by the at least one processor as per the defined routines. The internal components of the controller 110 are not explained for being state of the art, and the same must not be understood in a limiting manner. The controller 110 may also comprise communication units to communicate with external computer or server/cloud computer through wireless or wired means such as Global System for Mobile Communications (GSM), 3G, 4G, 5G, Wi-Fi, Bluetooth, Ethernet, serial networks, and the like. The controller 110 is implementable in the form of System-in-Package (SiP) or System-on-Chip (SOC) or any other known types. Examples of controller 110 comprises but not limited to, microcontroller, microprocessor, microcomputer, etc.

[0010] In accordance to an embodiment of the present invention, the correction factors are stored in the memory element 114 in the form of table or maps. The memory element 114 stores lambda based correction factors 116, ignition timing based correction factors 118, engine temperature based correction factors 120, intake manifold pressure based correction factors 122, exhaust temperature based correction factors 124 and overall correction factor. These correction factors are obtained after multiple iterations of testing under controlled dynamometer. The model is obtained after study of engine parameters data with the application of Machine Learning (ML) and Artificial Intelligence (AI) based processing techniques.

[0011] In accordance to an embodiment of the present invention, the engine is a spark ignited gasoline combustion engine. Further, the estimated quantity of NOx emission is used to estimate NOx stored in a Lean NOx Trap (LNT) of an exhaust conduit of the engine.

[0012] According to an embodiment of the present invention, the engine is part of vehicle selected from a group comprising a two-wheeler such as scooter, motorcycle, a three-wheeler such as an auto-rickshaw, a four-wheeler such as cars, multi-wheel vehicles and other vehicles such as snow mobiles or water sports vehicles.

[0013] According to an embodiment of the present invention, a working of the controller 110 is explained. Consider a lean burn gasoline engine with LNT catalyst system. The NOx emission are stored in the LNT catalyst when lambda is lean and stored NOx is purged when lambda is rich with the help of HC and CO. The controller 110 of the present invention aids in estimating the stored NOx in the catalyst without the help of NOx sensor. The controller 110 takes in real-time values of the sensors and processes through the model where correction factors are identified and applied to calculated fuel flow.

[0014] Fig. 2 illustrates a flow diagram of a method for estimating the quantity of Nitrogen Oxides (NOx) emission from the engine without using the dedicated sensor, according to the present invention. The method comprises plurality of steps of which a step 202 comprises receiving, by the controller 110, the input signals for engine parameters, the engine parameters are either measured from respective sensors or derived. The method is characterized by a step 204 comprises calculating, by the controller 110, the quantity of fuel flow into at least one cylinder of the engine. A step 206 comprises determining, by the controller 110, the correction factor for each of the measured engine parameter. A step 208 comprises estimating, by the controller 110, quantity of the NOx emission through the model by using the determined corrections factors and the calculated quantity of fuel flow. In the model, the method comprises multiplying the correction factors with the calculated quantity of fuel flow (such as in grams/second). The output 112 is obtained as the quantity of NOx emissions. The output 112 is later used by the controller 110 to control the emissions or as per the requirement.

[0015] According to the present invention, the engine parameters comprises engine-out lambda value, ignition timing, engine temperature, intake manifold pressure and exhaust temperature. The correction factors for each of the engine parameters are stored in the memory element 114 in the form of the map or the table. The engine is the spark ignited gasoline internal combustion engine. The method may also comprises a step of estimating NOx stored in the Lean NOx Trap (LNT) in the exhaust conduit of the engine. The NOx stored quantity is estimated using the already estimated quantity of NOx emission from the engine.

[0016] According to the present invention, an engine-out NOx model for gasoline engine is provided. The model is executed by the controller 110 based on the real-time inputs from the sensors corresponding to the engine parameters. The NOx emission quantity is measured/estimated without the help of dedicated NOx sensor.

[0017] It should be understood that embodiments explained in the description above are only illustrative and do not limit the scope of this invention. Many such embodiments and other modifications and changes in the embodiment explained in the description are envisaged. The scope of the invention is only limited by the scope of the claims.
, Claims:We claim:
1. A controller (110) to estimate a quantity of Nitrogen Oxides (NOx) emissions from an engine without using a dedicated sensor, said controller (110) configured to:
receive input signals for engine parameters, said engine parameters are either measured from respective sensors or estimated, characterized in that,
calculate a quantity of fuel flow into at least one cylinder of said engine,
determine a correction factor for each of said measured engine parameter, and
estimate quantity of said NOx emission through a model using said determined correction factors and said calculated quantity of fuel flow.

2. The controller (110) as claimed in claim 1, wherein said engine parameters comprises engine-out lambda value, ignition timing, engine temperature, intake manifold pressure and exhaust temperature.

3. The controller (110) as claimed in claim 1, wherein said correction factor are stored in a memory element (114) in the form of map or table.

4. The controller (110) as claimed in claim 1, wherein said engine is a spark ignited gasoline internal combustion engine.

5. The controller (110) as claimed in claim 1, wherein said estimated quantity of NOx emission is used to estimate NOx stored in a Lean NOx Trap (LNT) of an exhaust conduit of said engine.

6. A method for estimating a quantity of Nitrogen Oxides (NOx) emission from an engine without using a dedicated sensor, said method comprising the steps of:
receiving input signals for engine parameters, said engine parameters are either measured from respective sensors or estimated, characterized by,
calculating a quantity of fuel flow into at least one cylinder of said engine,
determining a correction factor for each of said measured engine parameter, and
estimating quantity of said NOx emission by a model by using said determined correction factors and said calculated quantity of fuel flow.

7. The method as claimed in claim 6, wherein said engine parameters comprises engine-out lambda value, ignition timing, engine temperature, intake manifold pressure and exhaust temperature.

8. The method as claimed in claim 6, wherein said correction factor are stored in a memory element (114) in the form of map or table.

9. The method as claimed in claim 6, wherein said engine is a spark ignited gasoline internal combustion engine.

10. The method as claimed in claim 6, comprises estimating NOx stored in a Lean NOx Trap (LNT) in an exhaust conduit of said engine.