Method for measuring vehicle pollutant emissions using an on-board system

Abstract

The invention relates to a method for determining the pollutant emissions of a vehicle using an on-board measurement system having a sensor (CAP) and a computer system including a generic model (MOD GEN) of the vehicle. The method is based on using the measurements and the model to determine the amount of pollutants.

Description

Technical Field

[0001] The present invention relates to the field of vehicle pollutant emission determination.

[0002] Emissions from private cars in the real world are a matter of concern to the public and legislators. Indeed, the latest case (Dieselgate and its progression) has unduly damaged the automotive industry by demonstrating that some automakers were dishonest about emissions controls. It has been demonstrated that different settings are used for certification and actual use. Background Art

[0003] In order to solve these problems and avoid further scandals, the homologation standards have been modified by bringing them closer to reality (WLTC cycle: Worldwide Harmonized Light Vehicle Test Procedure) and by systematically comparing the emissions obtained under laboratory conditions and under real conditions (RDE: Real Driving Emissions). Therefore, measurement systems have been developed that can be adopted on private cars and / or transport vehicles. These devices, known as PEMS (Portable Emission Measurement Systems), are large, expensive, fragile and require a lot of maintenance work because they have to meet the accuracy criteria defined by the standard. These devices are therefore designed to be used only by experts during vehicle development or on the occasion of homologation.

[0004] Furthermore, emission determination methods have been developed using models and without sensors. Patent application FR-3,049,653 (WO-17,174,239) describes this model-based method. Although satisfactory in terms of speed, ease of use and representativeness (the model is constructed with vehicle parameters), this method does not take into account the specific characteristics of each vehicle, especially those related to control and calibration strategies, and is not sufficient in itself to determine emissions within the regulatory environment of the automotive market without a measurement system.

[0005] In order to overcome these drawbacks, the patent application No. FR-18 / 51,330 relates to an on-board vehicle emissions measurement system. The on-board measurement system comprises at least one sensor arranged downstream of the aftertreatment system and an optional sensor inserted into the vehicle OBD (on-board diagnostics) port, and a computer device comprising a model. According to the invention, the pollutant emissions are determined based on signals from the sensors and on a model. The use of a model that takes into account the signals of at least one sensor allows an accurate and representative emissions determination to be obtained. In addition, the use of a model makes it possible to limit the number of sensors, which allows limiting the cost and maintenance of the on-board measurement system and provides ease of use. However, the on-board system does not allow the measurement of emissions in mass. In fact, the system allows the measurement of emissions in volume. In order to obtain this data (emissions in mass), a measurement of the flow at the outlet of the aftertreatment system is usually used (as is the case for PEMS systems), which makes the treatment system complex, bulky and expensive. Summary of the invention

[0006] The object of the invention is to determine (absolute) emissions in a simple, compact and economical manner. The invention therefore relates to a method for determining the polluting emissions of a vehicle using an onboard measurement system having sensors and a computer system including a generic model of the vehicle. The method is based on using measurements and models to determine the amount of pollutants. This avoids the need for a flow measurement system by determining the amount of carbon dioxide based on a generic model of the vehicle.

[0007] The invention relates to a method for determining the polluting emissions of a vehicle having travelled a route, said vehicle comprising an internal combustion engine and an aftertreatment system for the exhaust gases of said engine, said method implementing an on-board measurement system comprising at least one sensor arranged downstream of said aftertreatment system and a computer system for determining said emissions of said vehicle by implementing a generic model of said vehicle. For this method, the following steps are performed:

[0008] a) measuring the volume concentration of the pollutant emission downstream of the post-treatment system by means of the sensor,

[0009] b) estimating the fuel consumption of the vehicle by means of the general model of the vehicle,

[0010] c) determining a mass flow rate of carbon dioxide downstream of the aftertreatment system based on the estimated fuel consumption of the engine, and

[0011] d) determining emissions downstream of the aftertreatment system of the vehicle, said determination being performed based on said measurement of the volumetric concentration of said emissions and the mass flow of carbon dioxide determined therefrom.

[0012] According to one embodiment, the pollutant emissions of the vehicle are determined according to the following formula: pol =R mes ×K×Q CO2_est , Q pol is the emission, R mes is the measured volume concentration of the emission, K is a coefficient based on the molar mass ratio of the pollutant under consideration to carbon dioxide, Q CO2_est is the estimated CO2 mass flow rate.

[0013] According to one implementation, the general model of the vehicle includes a model of the vehicle, a model of the engine type of the vehicle, and a post-treatment model of the vehicle, the vehicle model relating the position and / or altitude and / or speed of the vehicle to the torque and speed of the engine, the engine type model relating the torque and the speed of the engine to emissions at an outlet of the engine, and the post-treatment model relating the emissions at the outlet of the engine to emissions at an outlet of the post-treatment system.

[0014] According to one aspect, the vehicle-mounted system comprises a sensor selected from nitrogen oxides NO x Sensor, nitric oxide NO sensor, nitrogen dioxide NO2 sensor, carbon monoxide CO sensor or carbon dioxide CO2 sensor, dioxygen O2 sensor, unburned hydrocarbon sensor, ammonia NH3 sensor, particle sensor.

[0015] Preferably, the onboard system includes a sensor plugged into a diagnostic port of the vehicle, and the at least one sensor communicates with the sensor plugged into the diagnostic port of the vehicle via a wireless connection.

[0016] Advantageously, the computer system comprises at least one smartphone, the at least one sensor communicating with the smartphone via a wireless connection.

[0017] Advantageously, the generic model of the vehicle contained in the computer system is stored in a cloud, the smartphone and / or the sensor plugged into the diagnostic port of the vehicle being configured to interact with the cloud.

[0018] According to a feature, the generic model of the vehicle further depends on at least one macro parameter (PAR) of the vehicle, preferably obtained from a database (BDD) and / or through an interface with a user.

[0019] Furthermore, the invention relates to a method for determining a dynamic compliance factor of pollutant emissions of a vehicle by means of the on-board measuring system, wherein the following steps are performed:

[0020] a) determining the pollutant emissions of the vehicle by means of a method for determining pollutant emissions according to one of the above features,

[0021] b) constructing a nominal model of the vehicle according to at least one macroscopic parameter of the vehicle by means of a machine learning algorithm, the nominal model of the vehicle corresponding to a theoretical model of the generic model of the vehicle, and

[0022] c) by converting the nominal emission value Q determined by the nominal model pol_nom and the emission value Q determined by the method for determining emissions according to one of the above characteristics pol_mes The dynamic compliance factor is determined by comparison.

[0023] The invention also relates to a method for determining a dynamic compliance factor of pollutant emissions of a vehicle by means of the on-board measurement system, wherein the following steps are performed:

[0024] a) determining the pollutant emissions of the vehicle by means of a method for determining pollutant emissions according to one of the above features,

[0025] b) constructing a nominal model of the vehicle according to at least one macroscopic parameter of the vehicle by means of a machine learning algorithm, the nominal model of the vehicle corresponding to a theoretical model of the generic model of the vehicle,

[0026] c) constructing, by means of a machine learning algorithm, a calibrated model of the vehicle from the determined polluting emissions, the measurements of the sensors and data from the generic model of the vehicle, the calibrated model of the vehicle corresponding to the generic model of the vehicle calibrated with the measurements of the sensors of the on-board measurement system, and

[0027] d) for the route travelled by the vehicle, by transforming the estimate Q of the pollutant emissions obtained by the calibrated model of the vehicle pol_cal and the estimate Q of the pollutant emissions obtained via the nominal model of the vehicle pol_nom The dynamic compliance factor is determined by comparison.

[0028] According to an embodiment, a dynamic compliance factor is determined for said route travelled by said vehicle by comparing pollution emissions measured by another measurement system with pollution emissions estimated by said nominal model of said vehicle.

[0029] Advantageously, the macroscopic parameters used to construct the nominal model include the certification standard of the vehicle.

[0030] According to an aspect, a dynamic compliance factor is determined for each segment of the route travelled by the vehicle, in particular each route segment has an equal length, preferably the length of the route segments ranges between 1 and 50 km.

[0031] According to an implementation of the invention, the method comprises the additional step of determining a dynamic compliance factor for a predetermined theoretical driving cycle by means of the nominal and calibrated model of the vehicle.

[0032] According to an alternative embodiment, said additional step of determining said compliance factor is repeated for a plurality of predetermined theoretical driving cycles and the driving cycle having the highest dynamic compliance factor is identified.

[0033] Furthermore, the invention relates to a method for identifying at least one most polluting vehicle, wherein the following steps are performed:

[0034] a) implementing a method for determining a dynamic compliance factor according to one of the above features for a plurality of vehicles, and

[0035] b) comparing the highest compliance factor of each vehicle to determine the at least one most polluting vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Other characteristics and advantages of the method according to the invention will become apparent from reading the following description of an embodiment given by way of non-limiting example, with reference to the accompanying drawings, in which:

[0037] Figure 1 The steps of a method according to an embodiment of the present invention are shown.

[0038] Figure 2 shows an on-vehicle measurement system that can be used by the method according to an embodiment of the present invention,

[0039] Figure 3 shows an on-vehicle measurement system that can be used by the method according to a second embodiment of the present invention,

[0040] Figure 4 The steps of the method according to the second embodiment of the present invention are shown.

[0041] Figure 5 The steps of the method according to the third embodiment of the present invention are shown.

[0042] Figure 6 The steps of constructing a calibrated model according to an example embodiment of the present invention are shown.

[0043] Figure 7 NO is shown for an example of a route travelled xemissions, the polluting emissions are determined by reconstructing the emissions in mass and by using the emission values ​​determined for a nominal behavior of the vehicle on the same route, and

[0044] Figure 8 The method for determining the dynamic compliance factor according to the present invention shows Figure 7 Dynamic conformity factor for the traveled route in the example of FIG. DETAILED DESCRIPTION

[0045] The invention relates to a method of determining polluting emissions of a vehicle having travelled at least one route.

[0046] The term "pollutant" designates nitrogen oxides (NO x ), nitrogen monoxide (NO) and nitrogen dioxide (NO2) (the two can advantageously be measured separately), particles, carbon monoxide (CO), carbon dioxide (CO2), unburned hydrocarbons (HC) and ammonia (NH3). The method according to the invention allows the determination of emissions of at least one of these pollutants (advantageously more than one and preferably all).

[0047] The vehicle comprises an internal combustion engine (hereinafter referred to as the "engine") and an aftertreatment system for the exhaust gases of the engine. The internal combustion engine may be a gasoline engine or a diesel engine, or an engine running on any other type of fuel. The engine may achieve propulsion of the vehicle alone, or it may be part of a hybrid propulsion system. The aftertreatment system allows the polluting emissions at the outlet of the engine to be treated, thereby reducing the polluting emissions of the vehicle. The aftertreatment system may include a three-way catalyst for simultaneously treating unburned hydrocarbons, carbon monoxide and nitrogen oxides, and / or an oxidation catalyst for treating unburned hydrocarbons and carbon monoxide, and / or a DeNO catalyst for reducing nitrogen oxides in the presence of oxygen. x Catalysts, and / or various filters for removing solid particles.

[0048] The method of determining polluting emissions uses an on-board emission measurement system. The term "on-board" indicates that the system is installed on the vehicle, which also implies that the system may be attached to the outside of the vehicle.

[0049] The method and the on-board measuring system according to the invention can be used in motor vehicles. However, the method and the measuring system can also be used in the following fields: road transport, two-wheeled vehicles, the railway sector, the marine sector, the aviation sector, hovercraft and amphibious vehicles, etc.

[0050] The vehicle-mounted measurement system according to the present invention comprises:

[0051] at least one sensor arranged at the outlet of the aftertreatment system, the sensor being designed to measure the volume concentration of gas or particles at the outlet of the aftertreatment system, and

[0052] A computer system for determining polluting emissions, the computer system thus implementing a generic model of the vehicle.

[0053] The generic model of the vehicle is a representative model of the vehicle, which model is configured to take into account the signals from the sensor(s) to determine emission-related values. The use of the model allows emissions to be determined with a limited number of sensors, which involves a reduction in costs and in the maintenance phases of the measurement system, and allows the on-board measurement system to be easily transportable and adaptable to all types of vehicles.

[0054] The generic model of a vehicle can be of any type.

[0055] According to an embodiment of the invention, a generic model of a vehicle may include three configured models that may be executed (sequentially) using a waterfall approach:

[0056] o a model of the vehicle, the vehicle model relating the vehicle's position and / or altitude and / or speed to engine torque and speed,

[0057] ○ an engine type model for the vehicle, which relates engine torque and speed to emissions at the engine outlet, and

[0058] o An aftertreatment model that relates pollutant emissions at the outlet of the engine to emissions at the outlet of the aftertreatment system.

[0059] According to an exemplary embodiment of the invention, the general model of the vehicle may be based on the model described in patent application FR-3,049,653 (WO-17,174,239). These three models are not described in detail in this application. For a detailed description of these models, reference may be made to patent application FR-3,049,653 (WO-17,174,239), in particular:

[0060] - Vehicle Model from page 8, line 29 to page 10, line 10,

[0061] -Engine Type Model from page 10, line 11 through page 12, line 24, and

[0062] - Post-processing model from page 12 line 26 to page 13 line 26.

[0063] According to one embodiment of the invention, the three models of the computer system may depend on macroscopic parameters of the vehicle. Thus, the model best represents the vehicle, the engine type and the aftertreatment system. Macroscopic parameters are understood to be general characteristics related to the vehicle, the engine or its aftertreatment system. These parameters are constant parameters of the vehicle corresponding to the vehicle manufacturing data. The parameters are called macroscopic parameters because they are determined at the scale of the vehicle, and they are not microscopic parameters determined at the scale of a grid cell representing a small part of the combustion chamber (for example in patent application FR-2,984,557 (US-2013-0,158,967)).

[0064] Macro parameters can be of three types:

[0065] - parameters related to the general configuration of the vehicle (e.g. vehicle mass, gearbox, etc.),

[0066] - engine-related parameters (e.g. injection type, displacement, engine type, etc.), and

[0067] -Parameters related to the post-processing system (e.g. post-processing type).

[0068] According to an embodiment of the present invention, at least one macro parameter may be obtained, and the at least one macro parameter is selected from:

[0069] -Engine type (petrol, diesel, etc.)

[0070] -Emission standard level (Euro 1, Euro 2, etc.)

[0071] -Engine displacement

[0072] -Maximum torque and associated engine speed

[0073] - Maximum power and associated engine speed

[0074] - Vehicle quality

[0075] -Vehicle transmission type (gearbox type and composition, etc.)

[0076] - Aftertreatment system type

[0077] -Injection system type

[0078] - Air cycle architecture (whether exhaust gas recirculation (EGR) is present, whether a turbocharger is used, whether supercharging is present, etc.)

[0079] -Wheel size, etc.

[0080] According to a variant embodiment, the macro parameters can be obtained from a database that lists various vehicles in service. For example, the macro parameters can be obtained by the registration number of the vehicle, and the database associates the license plate number with the design of the vehicle (brand, model, engine type, etc.) and includes the macro parameters of the vehicle. According to an example embodiment, the database can be stored in the cloud of the computer system.

[0081] Alternatively, the macro parameters may be manufacturing data provided by the user, in particular via an interface (eg a smartphone or a geolocation system).

[0082] According to one embodiment of the present invention, the computer system of the vehicle-mounted measurement system may include a smart phone. This smart phone provides installation convenience, adaptability, transportability and reduced cost in the vehicle relative to a dedicated computer or calculator. In addition, the smart phone allows the system to be used by a wide audience.

[0083] Alternatively, the on-board measurement system may comprise a sensor that is plugged into the OBD (on-board diagnostics) port of the vehicle and that can retrieve values ​​such as engine speed, engine temperature, water temperature or vehicle speed. In the remainder of the following description, this sensor is referred to as an OBD sensor. The computer device can then be designed to take into account the values ​​obtained by the OBD sensor. This OBD sensor may comprise a wireless connection device (e.g. GSM and / or Wi-Fi and / or Bluetooth) and / or a geographic location sensor (e.g. GPS type). This sensor equipped with a connection device allows the equipment to be streamlined, simple and compact, and the measurement accuracy is improved, and this enables the same even without a smartphone.

[0084] For ease of installation on the vehicle (without specific cables), the sensor(s) may communicate with the smartphone or OBD sensor via a wireless connection of the Wi-Fi or Bluetooth type, for example. In a variant, a wired connection may be provided between the sensor and the smartphone or OBD sensor or a computer or calculator.

[0085] In addition, the three models of the computer system can be stored in the cloud or online storage service. This allows limiting the memory consumed by the smartphone and using a more powerful processor to execute the three models. For this configuration, the smartphone or OBD sensor is configured to interact with the cloud through an Internet connection. This configuration using a smartphone or OBD sensor and the cloud enables simplified use at reduced cost.

[0086] If the smartphone or OBD sensor is equipped with a geolocation system (GPS), the smartphone or OBD sensor can also be configured to measure the speed and / or altitude and / or position of the vehicle. This position, speed or altitude data can be used in a generic model contained in the computer system, or perhaps (for embodiments with three models) in a vehicle model.

[0087] In a variation (for example in the case where the smartphone or OBD sensor is not equipped with a geolocation system), the in-vehicle system may include a geolocation sensor that communicates with the smartphone or OBD sensor.

[0088] According to another aspect, the computer system may further include a device for displaying the pollutant emissions determined by the model to inform the vehicle user of the emissions. For example, the display device may be a screen of a smartphone.

[0089] Instead of a smartphone or OBD sensor, the computer system may include a calculator or computer that communicates with the sensor(s). The calculator or computer may include a generic model of the vehicle (perhaps three models that make up the generic model of the vehicle).

[0090] According to the present invention, the method for determining pollutant emissions comprises the following steps which will be described in detail in the following specification:

[0091] 1) Measure the volume concentration of emissions

[0092] 2) Estimate vehicle fuel consumption

[0093] 3) Determine the carbon dioxide mass flow rate

[0094] 4) Identify pollutant emissions

[0095] Preferably, these steps can be performed by an on-board measurement system. Advantageously, steps 2) to 4) can be performed by a computer system of the on-board measurement system.

[0096] 1) Measuring volume concentration of pollutant emissions

[0097] This step comprises measuring, for at least one pollutant type, the volume concentration of the polluting emissions by means of sensors of the onboard measurement system. In practice, the sensor(s) of the onboard measurement system do not allow the measurement of absolute quantities by mass of the emissions downstream of the aftertreatment system, they only allow the measurement of relative values, namely the volume concentration of the emissions. Preferably, the volume concentration is expressed in percentage or parts per million (ppm).

[0098] According to one implementation of the present invention, the sensor may be selected from nitrogen oxides NO xsensor, nitric oxide NO sensor, nitrogen dioxide NO2 sensor, carbon monoxide CO sensor or carbon dioxide CO2 sensor, dioxygen O2 sensor, unburned hydrocarbons sensor, particle sensor or ammonia NH3 sensor.

[0099] Preferably, the on-board measurement system includes a carbon dioxide CO2 sensor, a particle sensor and a nitrogen oxide NO x This configuration provides a good compromise in terms of onboard system cost and measured data for optimal calibration of the model.

[0100] Specifically, the sensor(s) of the on-board measurement system may be selected from:

[0101] ○About OBD sensor:

[0102] Preferably, a sensor capable of reading information circulating on the vehicle's OBD communication network through a diagnostic port or OBD port arranged near the vehicle's dashboard;

[0103] ○About nitrogen oxides NO x Volume Sensor:

[0104] Preferably, an electrochemical sensor

[0105] Ultraviolet UV sensor

[0106] Infrared IR sensor, or

[0107] Chemiluminescence detector (CLD);

[0108] ○About carbon monoxide or carbon dioxide CO / CO2 volume sensor:

[0109] Preferably, an infrared IR sensor, or

[0110] Ultraviolet UV sensor;

[0111] ○About the oxygen volume sensor:

[0112] Preferably, an electrochemical sensor

[0113] Laser diode measurement

[0114] Paramagnetic sensor, or

[0115] Magnetic sensor;

[0116] ○About PM / PN / Opacity Sensor:

[0117] Preferably, charged particle scattering counts

[0118] Induction current measurement and counting

[0119] Particle accumulation sensor

[0120] Optical opacity meter (Beer-Lambert principle or Mie scattering)

[0121] ·Nucleus counting

[0122] Particle irradiation counting

[0123] Optical or ion home smoke detectors

[0124] BAM (Beta Attenuation Monitor) for air quality measurement, or

[0125] True laser particle counter for air quality measurement.

[0126] 2) Estimating vehicle fuel consumption

[0127] This step includes estimating the vehicle fuel consumption for the travel route by means of a generic model of the vehicle. According to an embodiment in which the generic vehicle model includes a vehicle model, an engine type model and a post-processing model, the vehicle fuel consumption for the travel route may be obtained at the output of the engine type model.

[0128] 3) Determining CO2 mass flow rate

[0129] This step comprises determining the mass flow of carbon dioxide CO2 downstream of the aftertreatment system from the vehicle fuel consumption estimated in the previous step for the route travelled by the vehicle. Thus, no mass flow measurement system is required to estimate the amount of CO2 at the outlet of the aftertreatment system.

[0130] According to an embodiment, the mass flow of CO 2 may be determined by a method based on combustion representation, carbon balance and by taking into account the fuel type.

[0131] Preferably, the carbon dioxide mass flow rate can be expressed in mass per unit time, for example in g / h.

[0132] 4) Identify pollutant emissions

[0133] This step comprises determining the emission of at least one type of pollutant from the measurement of the volumetric concentration of the exhaust downstream of the aftertreatment system performed in step 1) and from the carbon dioxide mass flow rate downstream of the aftertreatment system determined in step 3). Combining the volumetric concentration measurement with the estimate of the carbon dioxide mass flow rate allows the pollutant emissions to be accurately determined without using a flow measurement system downstream of the exhaust aftertreatment system. Thereby, the pollutant emissions are determined using an accurate, simple, economical and compact device.

[0134] According to an embodiment of the present invention, the pollutant emissions of a vehicle may be determined by a formula of the following type: Q pol =R mes ×K×Q CO2_est , where Q pol is the emission to be determined, R mes is the measured volume concentration of the pollutant emission (step 1)), K is a coefficient based on the molar mass ratio of the pollutant under consideration to carbon dioxide, and Q CO2_est is the estimated carbon dioxide mass flow estimated in step 3). This formula provides an accurate estimate.

[0135] Advantageously, the amount of polluting emissions can be expressed in mass per unit time, for example in g / h.

[0136] According to an embodiment of the invention, the method may comprise the additional step of storing and / or displaying the emissions thus determined. The data may be stored and / or displayed on the vehicle: on the dashboard, on a separate portable device such as a geolocation device (GPS type), a mobile phone (smartphone type), etc. The indicator may also be stored and displayed on a website that the driver can access after the drive. Furthermore, the polluting emissions may be shared with vehicle control stations, car sharing companies, car rental companies, fleet managers, etc.

[0137] Advantageously, the method according to the invention for determining pollutant emissions can be implemented in a simple (especially without the need for specialists), economical and compact manner.

[0138] Figure 1 The method for determining pollutant emissions according to an embodiment of the present invention is schematically illustrated by way of non-limiting example. First, the following steps are performed simultaneously or continuously:

[0139] -Measurement of the volume concentration R of the exhaust gas downstream of the aftertreatment system by means of a sensor (CAP) mes ,as well as

[0140] - Estimation of the mass flow of CO2 Q by means of a generic model of the vehicle (MOD GEN) and an intermediate step of determining the fuel consumption during the journey CO2_est .

[0141] Then combine (FUS) volume concentration R mes and the estimated carbon dioxide mass flow rate Q CO2_est To determine the amount Q of at least one type of pollutant discharged at the outlet of the aftertreatment system pol .

[0142] Figure 2By way of non-limiting example, a computer system of an on-board measurement system according to an embodiment of the invention is schematically shown, which allows the implementation of a method for determining polluting emissions. The on-board measurement system comprises a computer system SIN. The computer system SIN comprises a smartphone TEL and / or an OBD sensor and / or any similar device equipped with a wireless connection device (not shown) and a cloud NUA.

[0143] In this figure, the dashed arrows correspond to wireless connections between elements. The smartphone TEL and / or OBD sensor and / or any similar device interacts with the cloud NUA via, for example, a wireless connection, a GSM (Global System for Mobile Communications) connection. The smartphone and / or OBD sensor transmits a signal to the cloud NUA. Specifically, the smartphone TEL and / or OBD sensor may transmit geolocation measurements.

[0144] The generic model MOD GEN of the vehicle is stored in the cloud NUA. This model includes three models: the vehicle model MOD VEH, the engine model MOD MOT and the post-treatment model MOD POT. The computer system SIN executes these three models one by one through the data received by the smartphone to determine the pollutant emissions.

[0145] Figure 3 By way of non-limiting example, the use of a computer system of an on-board measurement system according to an embodiment of the invention for implementing a method for determining polluting emissions is schematically illustrated. In the figure, dashed lines indicate optional elements in the method.

[0146] Before executing the steps of the method, a generic model (MOD GEN) of the vehicle is constructed (including a vehicle model MOD VEH, an engine model MOD MOT and a post-processing model MOD POT). These models are preferably constructed according to the macro parameters PAR. Alternatively, the macro parameters PAR can be obtained from a database BDD listing various vehicles in circulation. For example, the macro parameters PAR can be obtained by inputting a vehicle registration number, and the database BDD associates the license plate number with the design of the vehicle (brand, model, engine type, etc.) and includes the macro parameters of the vehicle. The database BDD can be stored in the cloud NUA of the computer system.

[0147] A first series of macro parameters PAR1 may be used to construct the vehicle model MOD VEH. This first series of macro parameters PAR1 may include the following parameters: vehicle mass, maximum power and associated engine speed, maximum speed, gearbox type (non-limiting list).

[0148] The second set of macro parameters PAR2 may be used to build the engine model MOD MOT. This second set of macro parameters PAR2 may include the following parameters: displacement, engine type, maximum torque and power, air cycle architecture, vehicle certification standard (non-limiting list).

[0149] The third series of macro parameters PAR3 may be used to construct the post-treatment model MOD POT. The third series of macro parameters PAR3 may include the following parameters: displacement, vehicle certification standard (non-limiting list).

[0150] The first step may include performing a geolocation measurement step by means of a smartphone TEL and / or a sensor and / or any similar device (advantageously an OBD sensor). The vehicle's position pos may be measured in this step GPS and / or altitude alt GPS and / or speed V GPS . Consider the altitude alt GPS In particular, it allows the slope of the road to be taken into account. Preferably, three measurements are performed in order to have the most accurate information possible about the vehicle's geographical location, since driving style and vehicle acceleration can then be taken into account. The measurements can be made using a geolocation system (e.g., of the GPS (Global Positioning System) or Galileo type) or by means of a smartphone or the like. In the case of a smartphone, the latter may be equipped with a geolocation system, or the measurements may be performed by other means, in particular by triangulation.

[0151] Furthermore, a first step comprises transmitting the geolocation measurements to the cloud NUA.

[0152] An optional second step is to pre-process the measured signals PRT. This step allows improving the quality of the measured signals before using them. It is particularly interesting if the measurements are performed by a smartphone, since the measurements obtained with such a device may be somewhat imprecise. This pre-processing may be variable, since it depends on the quality of the input data. According to an embodiment of the invention, the pre-processing PRT may consist in oversampling the signal and then filtering it. At the end of this step, the position pos of the vehicle is obtained. GPS and / or altitude alt GPS and / or speed V GPS Relevant signals are therefore available, which have been preprocessed.

[0153] The third step consists in determining the engine torque and speed. This step is performed by the vehicle model MOD VEH, which is based on the geographical location data: the vehicle's position pos GPS and / or altitude alt GPS and / or speed V GPSTo determine the engine torque Cme and speed N e .

[0154] The fourth step consists in determining the pollutant emissions at the engine outlet; this step is performed by means of an engine model MODMOT which is based on the engine torque Cme and speed N e To determine the pollutant emissions PSME at the engine outlet.

[0155] The fifth step consists in determining the polluting emissions of the vehicle (i.e. at the outlet of the aftertreatment system). The emissions determination can be done at any time, for example at a frequency of 1 Hz. In addition, the cumulative emissions can also be determined for a given route. This step is performed using an aftertreatment model MOD POT, which determines the polluting emissions at the outlet of the aftertreatment system from the emissions at the outlet of the engine PSME.

[0156] The optional sixth step is related to data storage. Once the polluting emissions of the vehicle have been determined, these emissions can be stored STO (recorded), specifically in a database (different from the database including macro parameters). This storage STO can focus only on the polluting emissions of the vehicle, but it can also focus on the data determined after each step of the method: preprocessed measurements and / or the torque Cme and speed N of the engine. e and / or the polluting emissions PSME at the engine outlet. This information enables monitoring of the actual use and the associated emissions with good control and time resolution. The storage STO can be included in the cloud NUA.

[0157] Furthermore, the invention relates to a method for determining a dynamic compliance factor for the pollutant emissions of a vehicle for a travel route. A dynamic compliance factor is understood to be a coefficient that indicates the behavior of the vehicle in terms of emissions, which coefficient is the result of a comparison between a theoretical emission value and a measured and / or estimated emission value. The method for determining a dynamic compliance factor for pollutant emissions uses a method for determining pollutant emissions according to any of the variants of the invention described above.

[0158] For this method, perform the following steps:

[0159] 1) Identify pollutant emissions

[0160] 2) Build a nominal model

[0161] 3) (Optional Step) Build a Calibrated Model

[0162] 4) Determine the dynamic compliance factor

[0163] Preferably, these steps are performed by an on-board measurement system. Advantageously, steps 1) to 4) can be performed by a computer system of the on-board measurement system.

[0164] 1) Identify pollutant emissions

[0165] This step consists in determining, for at least one pollutant type, the emissions (in mass) for the route travelled by the vehicle by means of a method for determining pollutant emissions according to one of the variants or one of the combinations of variants described above.

[0166] 2) Constructing the nominal model

[0167] This step includes constructing a nominal model of the vehicle based on at least one macro parameter of the vehicle by a machine learning algorithm. The nominal model of the vehicle corresponds to a theoretical model of a universal vehicle model of ideal operation of the vehicle. In other words, the nominal model of the vehicle represents a defect-free vehicle that meets its corresponding standard.

[0168] According to an embodiment of the present invention, the macro parameters used to construct the nominal model may be vehicle certification standards (eg, Euro 4, Euro 5, etc.).

[0169] According to an implementation of the invention (which can be combined with the previous embodiment), the macro parameters used to construct the nominal model may include manufacturing data related to the vehicle.

[0170] These macro parameters may be supplemented by information about the driver's use of the vehicle (eg engine speed, engine load). This information may be acquired by OBD sensors.

[0171] 3) Building a calibrated model

[0172] This optional step (for a third embodiment of the invention) consists in constructing a calibrated model of the vehicle from the determined polluting emissions, measurements from the onboard system sensors and data from a generic model of the vehicle. The calibrated model corresponds to a generic model of the vehicle calibrated with the measurements of the sensors. The construction of the calibrated model according to the invention is performed by a machine learning algorithm.

[0173] Calibration of the generic model can be performed for several parameters, which come from (non-exhaustive list):

[0174] - The gear ratio of the vehicle;

[0175] - Calibration of engine warm-up dynamics via engine water temperature;

[0176] - Calibration of fuel consumption;

[0177] - calibration of the combustion gas cycle in the case of spark-ignition engines (e.g. gasoline engines);

[0178] - NO of nitrogen oxides xThe value allows calibration of the light-off / preheating of the three-way catalyst;

[0179] -Nitrogen oxides NO x Value allows calibration with NO x Models related to reduction catalysts: NO x NO in the trap case x Storage model, injection of reducing agent (mainly ammonia) and storage model in the case of SCR (Selective Catalytic Reduction) catalysts;

[0180] - The measured particle values ​​allow calibration of the soot emission model in the case of engines without exhaust gas filtration systems;

[0181] - In the case of engines with an exhaust gas filtration system, particle measurement allows the filtration efficiency to be assessed.

[0182] According to an example implementation of this step, the portion of the generic vehicle model representing the gearbox staging can be calibrated using data from the OBD sensor and the engine speed signal. For this application, the generic vehicle model can be calibrated using vehicle power and maximum achievable speed. The gearbox staging can first be derived using conventional design principles. The data from the generic vehicle model then allows a grouping method to be applied that identifies the staging ratios and gear ratios that are engaged throughout the route of travel.

[0183] According to another example of implementation of this step (which can be combined with the first example), this step can achieve the nitrogen oxide NO of diesel vehicle exhaust gas. x Calibration of the estimate. For example, in order to estimate the pollutant emissions downstream of the aftertreatment system, the generic vehicle model can rely on a model of the emissions at the engine outlet and a model of the aftertreatment system. The estimated internal physical quantities can be used to obtain the emissions at the engine outlet, which may be in particular nitrogen oxides NO x , particles, carbon monoxide, and carbon dioxide. Specifically, NO x Emissions (NO x EO) can depend on the fuel flow Q fuel and the combustion gas ratio BGR in the cylinder, and can be written as follows:

[0184]

[0185] A library of aftertreatment models has been developed with several sub-models (see the aftertreatment models in patent application FR-3,049,653 (WO-17,174,239)). With these sub-models, most existing exhaust pipe architectures (aftertreatment systems) can be described. The output of these sub-models is the pollutant emissions at the outlet of the aftertreatment system. These two elements allow to improve the pollutant estimation at the outlet of the system, by the pollutant level required for the vehicle and by the data fusion with the sub-models. For example, Figure 6 shows the implementation for building a post-treatment system downstream of NO x Steps for calibrating the model of emissions. NO at engine outlet x Emissions (NO x EO), the combustion gas ratio in the cylinder, the average overall efficiency of the aftertreatment system (specifically, the catalytic system SCR) (expressed by SCR Eff generic), and the NO x Emissions (NO x TP) is determined in the general model MOD GEN. In parallel, the NOx emissions (NO x TP). Based on the measured CAP and the data from the generic model MOD GEN, the target CIB is determined for the quantity considered: the target for NOx emissions at the engine outlet (NO x EO target), the average efficiency target of the after-treatment system (SCR Eff target), and the NOx emission target at the outlet of the after-treatment system (NO x TP target). These targets are determined by the calibration machine learning algorithm CAL by determining the combustion gas ratio offset (BGR offset ) and the average efficiency gain of the aftertreatment system. For example, the ratio between the average overall efficiency and the average efficiency target allows the model to be calibrated. This step allows a calibrated model to be obtained that determines the NO at the engine outlet consistent with the measurements. x Emissions (NO x EO), the combustion gas ratio in the cylinder, the average efficiency of the aftertreatment system, and the NOx emissions (NO x TP).

[0186] The following equations can be used for these steps:

[0187] NO x TP target = NO x TP meas

[0188]

[0189]

[0190] BGR offset =1 / α×log(NO x EO target / NO x EO generic)×K0

[0191] Where K0 is NO x Model calibration coefficient, and Prop EO is NO x A coefficient of proportion that is assigned to changes in engine outlet or aftertreatment system efficiency.

[0192] 4) Determining the dynamic compliance factor

[0193] This step comprises determining a dynamic compliance factor (also referred to as dynamic compliance factor) by comparison between theoretical pollutant emission values ​​and measured and estimated pollutant emission values. The dynamic compliance factor is determined for the route travelled by the vehicle. A high value of the dynamic compliance factor reflects a vehicle whose behaviour (in terms of pollutant emissions) barely corresponds to a nominal vehicle (no defects, no faults); on the other hand, a low compliance factor value reflects a vehicle whose behaviour (in terms of pollutant emissions) corresponds to a nominal vehicle (no defects, no faults). Thus, a faulty vehicle can be determined by the dynamic compliance factor.

[0194] Advantageously, a dynamic compliance factor may be determined for each contaminant type under consideration.

[0195] According to a second embodiment (for which step 3 is not necessary), the dynamic compliance factor can be determined by comparing a nominal pollutant emission value determined via a nominal model with a pollutant emission value estimated based on measurements obtained from on-board system sensors, for example by a method for determining pollutant emissions based on any of the above-mentioned variants or combinations of variants.

[0196] For this first variant embodiment, the dynamic compliance factor CF may be calculated for at least one pollutant type by a formula of the following type: Where Q pol_mes The amount of pollutants estimated by determining emissions based on measurements obtained from onboard system sensors, Q pol_nom is the amount of pollutant estimated using the nominal model.

[0197] According to a third embodiment (for which step 3) is not essential), the dynamic compliance factor may be derived by comparison of theoretical pollutant emission values ​​obtained with a nominal model with values ​​measured by the sensor(s) and / or pollutant emissions estimated with a calibrated model.

[0198] For this third embodiment, the dynamic compliance factor CF may be calculated for at least one pollutant type by a formula of the following type: Where Q pol_cal is the amount of pollutant estimated using the calibrated model, and Q pol_nom is the amount of pollutant estimated using the nominal model.

[0199] Alternatively, the dynamic compliance factor CF can be determined by comparing the theoretical pollutant emission values ​​obtained via the nominal model with the values ​​measured via another measurement system (e.g. PEMS). In this case, the dynamic compliance factor CF can be calculated for at least one pollutant type by a formula of the following type: Where Q pol_pems is the amount of pollutant measured by another measurement system, and Q pol_nom is the amount of pollutant estimated using the nominal model.

[0200] According to one embodiment, a dynamic compliance factor may be determined for a travel route.

[0201] Additionally or alternatively, the dynamic compliance factor may be determined for at least one segment of the travel route (i.e. a portion of the travel route). Thus, the dynamic compliance factor may be determined for a single type of road (urban, suburban, motorway). Preferably, the dynamic compliance factor may be determined for each segment of the travel route in order to determine the behavior of the vehicle over the entire route. Advantageously, the route segment may have a constant length ranging between 1 and 50 km, advantageously between 5 and 25 km, preferably between 10 and 20 km, to represent the road type.

[0202] According to an aspect of the invention, this step may include an additional sub-step of determining at least one dynamic compliance factor for at least one theoretical driving cycle by means of a calibrated model and a nominal model. This sub-step includes determining a dynamic compliance factor for a driving cycle that the vehicle has not yet driven. The theoretical driving cycle may be a certification driving cycle or an emissions test driving cycle (e.g. a real driving emissions RDE cycle). Data related to the pollution behavior of the vehicle under other driving conditions may thereby be obtained.

[0203] Advantageously, the method may comprise repeating the sub-step of determining at least one dynamic compliance factor for several driving cycles, then identifying the driving cycle with the highest compliance factor. Thus, the worst case scenario (i.e. the worst driving cycle) in which the vehicle has a behavior (in terms of pollutant emissions) that is far from a nominal vehicle (without faults) can be determined.

[0204] Preferably, for this implementation of the invention, the dynamic compliance factor can be determined according to the third embodiment of the invention, i.e. by comparing the pollutant emissions estimated via the calibrated model and the nominal model. Using the calibrated model for the route traveled provides an estimate representative of the vehicle for other driving cycles (not yet performed). Thus, by means of a model calibrated with measured data, the dynamic compliance factor is accurate even for theoretical driving cycles.

[0205] According to an embodiment of the invention, the method may comprise the additional step of storing and / or displaying the dynamic compliance factor thus determined. The storage and / or display may be implemented on the vehicle: on the dashboard, on a separate portable device such as a geolocation device (GPS type), a mobile phone (smartphone type), etc. The indicator may also be displayed on a website that the driver can access after driving. Furthermore, the dynamic compliance factor(s) may be shared with a vehicle control station, a car sharing company, a car rental company, a fleet manager, etc.

[0206] Furthermore, the invention relates to a method for identifying at least one very polluting vehicle. The following steps are performed in the method:

[0207] a) implementing, for a plurality of vehicles, a method for determining a dynamic compliance factor for a number of theoretical driving cycles according to any of the variants or combinations of variants described above, and

[0208] b) Comparing the highest dynamic compliance factor for each vehicle and inferring therefrom the most polluting vehicle or vehicles.

[0209] The method allows the identification of one or more vehicles from a fleet of vehicles that are the most polluting. This identification then allows the selection of one or more vehicles on which a more complete test (e.g. a PEMS type test) needs to be performed, thereby avoiding lengthy, expensive and complex testing of vehicles that do not need this test.

[0210] Figure 4 The steps of the method for determining a dynamic compliance factor according to a second embodiment are schematically illustrated by way of non-limiting example. The lower part of the figure shows the construction of a nominal model MOD NOM based on a generic model MOD GEN and macro parameters (e.g. vehicle certification standards). As shown in the figure, the construction of the nominal model MOD NOM can further take into account signals from OBD sensors. As shown in Figure 1 The nominal model MOD NOM allows to determine the amount of CO2 at the outlet of the aftertreatment system: Q CO2 This data is consistent with the measured R from the sensor CAP mes Together they are used to determine the pollutant amount Q in the data fusion (reconstruction) step FUS pol_mes The pollutant emissions at the output of the nominal model MOD NOM are given by Qpol_nom denoted by, and these pollutant emissions are then compared with the pollutant quantity Q estimated by the method for determining emissions according to the invention pol_mes Compare with COMP to determine the dynamic compliance factor CFD.

[0211] Figure 5 The steps of the method for determining a dynamic compliance factor according to a third embodiment are schematically shown by way of non-limiting example. For this embodiment, the nominal model MOD NOM is represented by Figure 4 The calibrated model MOD CAL is constructed in a similar manner to the first variant embodiment of . Furthermore, the calibrated model MOD CAL is constructed by means of a generic model (not shown) and measurements (not shown). The nominal model MOD NOM allows the nominal emission quantity Q to be determined. pol_nom The calibrated model MOD CAL allows the determination of the calibrated emissions Q pol_cal The two pollutant emission quantities are then compared COMP to determine the dynamic compliance factor CFD.

[0212] Example

[0213] The features and advantages of the method according to the invention will become clear by reading the application examples below.

[0214] This example relies on testing of a Euro 6b vehicle. The method of determining a dynamic compliance factor is applied to a distance of approximately 90 kilometres travelled by the vehicle. A dynamic compliance factor is determined for each 10 kilometre travelled route segment.

[0215] Figure 7 The dashed speed curve V and the estimated NO are shown as a function of the distance D in kilometers traveled by the vehicle. x Emissions (in mg / km). NO x Emissions are represented by histograms: the light grey rectangles correspond to NO estimated using the nominal model. x Emissions Q pol_nom , while the dark grey rectangle corresponds to the Figure 1 The first embodiment of the method for determining pollutant emissions is to estimate NO x Emissions, which are denoted as Q pol_mes The speed profile is variable: the profile includes a first low-speed segment (10 to 20 km) that may correspond to an urban route, a second medium-speed segment (20 to 60 km) that may correspond to a suburban route, and a third high-speed segment (60 to 90 km) that may correspond to a highway route. x The emissions vary depending on the model used and the vehicle speed. In particular, it is observed that the vehicle emits more pollutants Q than expected. pol_nom The vehicle has a high pollution emission Q corresponding to the expected pollution emission Q in the second section.pol_nom of polluting emissions, and for the third highway section, the vehicles have faults in terms of emissions.

[0216] Figure 8 Shown according to Figure 7 The histogram of the dynamic conformity factor CF as a function of distance constructed from the data of is constructed. The dynamic conformity factor CF is obtained by the first variant embodiment (see Figure 4 ) and through the estimated NO x Q pol_mes Compared with the NO estimated by the nominal model x Q pol_nom The histogram confirms that Figure 7 Analysis: The vehicles surveyed on the third expressway section had faulty emissions.

Claims

1. A method for determining polluting emissions of a vehicle having travelled a route, said vehicle comprising an internal combustion engine and an aftertreatment system for the exhaust gases of said engine, said method implementing an on-board measurement system comprising at least one sensor (CAP) arranged downstream of said aftertreatment system and a computer system (SIN) for determining said emissions of said vehicle by implementing a generic model (MOD GEN) of said vehicle, said method being characterized by carrying out the following steps: a) measuring the volume concentration R of the pollutant emission downstream of the post-treatment system by means of the sensor (CAP) mes ; b) estimating the fuel consumption of the vehicle by means of the general model of the vehicle; c) determining a mass flow rate of carbon dioxide downstream of the aftertreatment system based on the estimated fuel consumption of the engine; as well as d) determining the emission Q downstream of the aftertreatment system of the vehicle based on the measurement of the volume concentration of the emission and the mass flow rate of carbon dioxide determined therefrom pol , The emissions of the vehicle are determined by the formula: Q pol =R mes ×K×Q CO2_est , where Q pol is the emission, R mes is the measured volume concentration of the emission, K is a coefficient based on the molar mass ratio of the pollutant emission under consideration to carbon dioxide, Q CO2_est is the estimated carbon dioxide mass flow rate.

2. The method according to claim 1, characterized in that The generic model of the vehicle comprises a model of the vehicle (MOD VEH), a model of the engine type of the vehicle (MOD MOT), and a post-treatment model of the vehicle (MODPOT), wherein the vehicle model (MOD VEH) relates the position and / or altitude and / or speed of the vehicle to the torque and speed of the engine, the engine type model (MOD MOT) relates the torque and the speed of the engine to the emissions at the outlet of the engine, and the post-treatment model (MOD POT) relates the emissions at the outlet of the engine to the emissions at the outlet of the post-treatment system.

3. The method according to claim 1, characterized in that The vehicle-mounted measurement system includes a sensor selected from nitrogen oxides NO x Sensor, nitric oxide NO sensor, nitrogen dioxide NO2 sensor, carbon monoxide CO sensor or carbon dioxide CO2 sensor, dioxygen O2 sensor, unburned hydrocarbon sensor, ammonia NH3 sensor, particle sensor.

4. The method according to claim 1, characterized in that The on-board measurement system comprises a sensor inserted into a diagnostic port (OBD) of the vehicle, the at least one sensor (CAP) communicating with the sensor inserted into the diagnostic port (OBD) of the vehicle via a wireless connection.

5. The method according to claim 1, characterized in that The computer system comprises at least one smart phone, and the at least one sensor (CAP) communicates with the smart phone (TEL) via a wireless connection.

6. The method according to claim 5, characterized in that The generic model of the vehicle contained in the computer system (SIN) is stored in a cloud (NUA), and the smartphone (TEL) and / or the sensor plugged into the diagnostic port (OBD) of the vehicle are configured to interact with the cloud (NUA).

7. The method according to claim 1, characterized in that The generic model of the vehicle further depends on at least one macro parameter (PAR) of the vehicle, obtained from a database (BDD) and / or through an interface with a user.

8. A method for determining a dynamic compliance factor of pollutant emissions of a vehicle by means of the on-board measurement system, wherein the following steps are performed: a) determining the pollutant emissions of the vehicle by means of a method for determining pollutant emissions according to one of claims 1 to 7; b) constructing, by means of a machine learning algorithm, a nominal model (MOD NOM) of the vehicle according to at least one macroscopic parameter of the vehicle, the nominal model (MOD NOM) of the vehicle corresponding to a theoretical model of the generic model (MODGEN) of the vehicle; and c) by converting the nominal emission value Q determined by the nominal model pol_nom and an emission value Q determined by a method for determining emissions according to one of claims 1 to 7 pol_mes The dynamic compliance factor (CFD) is determined by comparison.

9. The method according to claim 8, characterized in that A dynamic compliance factor (CFD) is determined for the route travelled by the vehicle by comparing the pollutant emissions measured by another measurement system with the pollutant emissions estimated by the nominal model (MOD NOM) of the vehicle.

10. The method according to claim 8, characterized in that The macro parameters used to construct the nominal model include the certification standards of the vehicle.

11. The method according to claim 8, characterized in that A compliance factor for dynamics (CFD) is determined for each segment of the route travelled by the vehicle, wherein each route segment has an equal length, the lengths of the route segments ranging between 1 and 50 km.

12. The method according to claim 8, characterized in that The method comprises the additional step of determining a dynamic compliance factor (CFD) for a predetermined theoretical driving cycle by means of the nominal model (MOD NOM) and a calibrated model (MOD CAL) of the vehicle.

13. The method according to claim 12, characterized in that Said additional step of determining said compliance factor (CFD) is repeated for a plurality of predetermined theoretical driving cycles and the driving cycle having the highest dynamic compliance factor (CFD) is identified.

14. A method for determining a dynamic compliance factor of pollutant emissions of a vehicle by means of said on-board measurement system, wherein the following steps are performed: a) determining the pollutant emissions of the vehicle by means of a method for determining pollutant emissions according to one of claims 1 to 7; b) constructing a nominal model (MOD NOM) of the vehicle according to at least one macro parameter of the vehicle by means of a machine learning algorithm, the nominal model (MOD NOM) of the vehicle corresponding to a theoretical model of the generic model (MODGEN) of the vehicle; c) constructing, by means of a machine learning algorithm, a calibrated model of the vehicle (MOD CAL) from the determined polluting emissions, the measurements of said sensors (CAP) and data from said generic model of the vehicle (MOD GEN), said calibrated model of the vehicle (MOD CAL) corresponding to said generic model of the vehicle (MOD GEN) calibrated with said measurements of said sensors (CAP) of said on-board measurement system; and d) for the route travelled by the vehicle, by transforming the estimate Q of the pollutant emissions obtained by the calibrated model (MOD CAL) of the vehicle pol_cal and the estimate of the pollutant emissions obtained via the nominal model (MOD NOM) of the vehicle pol_nom The dynamic compliance factor (CFD) is determined by comparison.

15. The method according to claim 14, characterized in that A dynamic compliance factor (CFD) is determined for the route travelled by the vehicle by comparing the pollutant emissions measured by another measurement system with the pollutant emissions estimated by the nominal model (MOD NOM) of the vehicle.

16. The method according to claim 14, characterized in that The macro parameters used to construct the nominal model include the certification standards of the vehicle.

17. The method according to claim 14, characterized in that A compliance factor for dynamics (CFD) is determined for each segment of the route travelled by the vehicle, wherein each route segment has an equal length, the lengths of the route segments ranging between 1 and 50 km.

18. The method of claim 14, wherein: The method comprises the additional step of determining a dynamic compliance factor (CFD) for a predetermined theoretical driving cycle by means of the nominal model (MOD NOM) and a calibrated model (MOD CAL) of the vehicle.

19. The method according to claim 18, characterized in that Said additional step of determining said compliance factor (CFD) is repeated for a plurality of predetermined theoretical driving cycles and the driving cycle having the highest dynamic compliance factor (CFD) is identified.

20. A method of identifying at least one most polluting vehicle, wherein the following steps are performed: a) implementing the method for determining a dynamic compliance factor (CFD) as claimed in claim 13 or 19 for a plurality of vehicles; and b) comparing the highest conformity factor (CFD) of each vehicle to determine the at least one most polluting vehicle.

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