TECHNICAL ARTICLE | How Does IRLAM™ Achieve High-Accuracy Gas Measurement?
Adapted from a technical article by Joshua Israel, Applications Engineering and Technical Marketing Manager, HORIBA Instruments, Inc. This version has been edited and reorganized for web readability, with key takeaways and frequently asked questions added.
Abstract
HORIBA’s Infrared Laser Absorption Modulation (IRLAM™) technology combines a wavelength-selective Quantum Cascade Laser (QCL), compact multi-pass Herriott Cell and proprietary signal-processing algorithms to measure low concentrations of exhaust gas components.
This article explains how these technologies work together to improve sensitivity, reduce interference and support rapid measurement during vehicle and engine development, aftertreatment evaluation, certification preparation and on-road emissions testing.
Accurately measuring vehicle and engine exhaust requires more than detecting whether infrared light has been absorbed. Samples can contain water vapor and numerous components with overlapping absorption characteristics. Concentrations may be low at the tailpipe yet change rapidly during acceleration, deceleration, cold-start operation and other transient test conditions.
A measurement system must distinguish the target component from interfering gases, maintain sufficient sensitivity at low concentrations and calculate concentration quickly enough to follow changes in the exhaust stream. These requirements affect laboratory certification testing as well as powertrain development, catalyst evaluation and Real Driving Emissions (RDE) measurements conducted outside the test cell.
IRLAM was developed to address these challenges by combining purpose-designed optical hardware with a proprietary concentration calculation method. Rather than treating the laser, gas cell and calculation algorithm as separate elements, HORIBA developed them as three connected technology pillars.
IRLAM is based on infrared absorption spectroscopy. Gas molecules absorb light at characteristic wavelengths, and the resulting absorption signal can be used to determine the concentration of a target component.
IRLAM applies this principle through three technologies developed specifically for gas measurement:
Together, these technologies support sensitive, selective and rapid measurement without requiring a large optical cell or a high-performance external computer. This combination allows the same underlying measurement principle to be incorporated into laboratory analyzers and more compact systems intended for portable or on-board testing.
Figure 1: The three technology pillars of IRLAM™ and the measurement characteristics they support.
Quantum Cascade Laser for Selective Gas Measurement
Figure 2: Schematic representation of a target gas absorption feature and absorption from a potentially interfering gas.
Each exhaust gas component absorbs specific wavelengths of light. This characteristic forms the foundation of absorption spectroscopy, in which the measured absorption signal is used to determine gas concentration.
HORIBA modulates the wavelength of a QCL around a target gas’s absorption peak. Structural and temperature control allow precise adjustment of the laser wavelength within the mid-infrared region of 3–10 μm.
This narrow wavelength window enables accurate concentration measurement while minimizing interference from other gases. Figure 2 illustrates the target gas absorption signal alongside absorption from interfering gases.
HORIBA develops, designs and manufactures its QCL specifically for gas measurement. The laser incorporates innovations that minimize optical-interference noise and reduce oscillation wavelength shifts caused by ambient temperature changes—two challenges associated with laser-based gas analysis.
Compact Herriott Cell and Optical Path Length
Advancements in optical hardware also support improvements in the gas measurement cell. HORIBA’s Herriott Cell maintains a long optical path while reducing the cell’s physical footprint.
The cell uses spherical mirrors to reflect the laser beam repeatedly through the sample gas. The high directivity of the QCL enables an extended optical path within a compact cell while maintaining the signal needed for sensitive measurement.
This extended path increases interaction between light and gas molecules, improving sensitivity to low gas concentrations. The compact cell also supports rapid measurement at low gas flow rates, helping achieve precise measurements across a wide concentration range.
Figure 3: Internal structure and exterior of the IRLAM Herriott Cell. Multiple reflections extend the optical path within a compact cell.
IRLAM offers an approach to NOx measurement that is particularly relevant to automotive emissions testing. It uses QCLs that emit light in the mid-infrared region, where NO and NO2 molecules strongly absorb light.
Compared with conventional infrared methods that use a broadband light source, IRLAM uses a component-specific laser and a narrow, focused wavelength window. This reduces cross-gas interference and limits the spectral information required for concentration calculation.
Each gas component has a dedicated light source. For NOx measurement, this enables direct measurement of NO and NO2 without an NO2-to-NO converter.
Figure 4: Conceptual measurement principle for feature-quantity extraction and interference correction.
IRLAM also differs from conventional chemiluminescence detector (CLD) systems used to determine total NOx. CLD systems typically convert NO₂ to NO before measurement. IRLAM measures both components directly through their infrared absorption characteristics, removing the converter from the measurement chain.
An SAE technical paper on IRLAM NOx measurement from diluted light-duty vehicle exhaust compares IRLAM with conventional CLD measurements using certification-quality emissions data.
For background on the conventional measurement principle, learn how chemiluminescence is used for NOx measurement.
Extracting meaningful information from raw absorption signals is essential to accurate concentration measurement. HORIBA’s concentration calculation algorithm enhances precision and sensitivity by isolating selected characteristics, called feature quantities, from the measured signal.
Unlike conventional intra-pulse methods that require large datasets and high-performance computers, IRLAM uses significantly less data while retaining the information needed for accurate measurement. This enables concentration calculation using a smaller embedded processor.
Extracting Feature Quantities
HORIBA’s approach modulates the QCL wavelength around a target gas’s absorption peak. The resulting absorption signal is correlated with predetermined feature reference signals, enabling interference correction similar in principle to that used in pneumatic detector-type NDIR gas sensors.
* Figure 5: Comparison of conventional spectrum-fitting and IRLAM feature-based concentration calculation.
When the QCL wavelength is modulated around the target gas’s absorption peak, the detector output signal D(t) changes according to the sample gas’s absorption spectrum.
Applying a logarithmic transformation to D(t) and removing the direct-current (DC) component produces the absorption-modulated signal A(t).
The feature quantities Sᵢ are then derived by correlating A(t) with feature reference signals Fᵢ(t) over the modulation period T, where i = 1, 2, …, n, and n is a positive integer.
* Reference: K. Shibuya et al., “High-sensitivity and low-interference gas analyzer with feature extraction from mid-infrared laser absorption-modulated signal,” Measurement Science and Technology, 32, 035201 (2021).
Correcting for Interfering Gases
Reference feature quantities are measured in advance for the target gas and relevant interfering gases.
By comparing the sample’s feature quantities with these reference relationships, the system determines the contribution of each component and calculates the target gas concentration.
This feature-based approach provides interference correction using fewer variables than conventional spectral curve fitting.
Reducing Calculation Time
Conventional spectral curve fitting uses hundreds of spectral data points to calculate concentration. IRLAM compresses the relevant spectral information into a small set of feature quantities, allowing concentration to be calculated using only a few numerical values.
The reduced dataset does not compromise measurement accuracy because the feature quantities retain the information necessary for measurement.
Figure 6: Simplified comparison of infrared gas measurement approaches, including IRLAM™.
Conventional spectral curve fitting can require solving several hundred simultaneous linear equations. IRLAM reduces this to approximately ten equations, shortening calculation time by a factor of approximately 10–100, as described in the original technical article.
An embedded processor therefore provides sufficient performance even for fast, real-time concentration calculation. This enables the development of compact analyzers without bulky external computing systems.
Learn more about the IRLAM concentration calculation algorithm
The interaction between IRLAM’s optical hardware and calculation algorithm supports several characteristics relevant to vehicle and engine emissions measurement.
IRLAM-equipped analyzers support the measurement of multiple exhaust components across laboratory, portable and on-board mobility applications.
Components Measured | Mobility Applications |
|---|---|
Available Components depend on the analyzer, optical configuration and intended application.
| Available configurations support applications throughout vehicle and engine development:
|
HORIBA applies IRLAM™ technology across laboratory, portable and on-board measurement systems for vehicle and engine emissions testing.
Quantum Cascade Lasers emit light in the mid-infrared region, where many exhaust gas components have strong absorption features. By tuning the laser around a selected feature, the measurement system can target a specific component while limiting the influence of nearby absorption from coexisting gases.
A Herriott Cell reflects the laser beam multiple times through the sample gas. This creates a long optical path within a compact physical space, increasing interaction between the laser light and gas molecules without requiring a correspondingly large measurement cell.
IRLAM combines component-specific wavelength selection with feature-based signal processing. The calculation algorithm compares selected characteristics of the measured absorption signal with reference features for the target and interfering gases, helping estimate each component’s contribution to the signal.
Sensitivity depends on several factors, including the target gas and selected absorption feature, laser performance, optical path length, sample pressure, measurement range, detector performance and signal-processing method. Detection limits should therefore be evaluated for the specific analyzer and configuration.
Quantum cascade laser measurement can support rapid analysis because it targets a limited wavelength region rather than processing a complete broadband spectrum. In IRLAM, the compact gas cell and feature-based calculation method also help the analyzer follow changing concentrations during transient engine cycles and on-road testing. Actual response characteristics depend on the analyzer and sampling configuration.
High-accuracy gas measurement depends on the complete measurement chain: how the light is generated, how it interacts with the sample and how the resulting signal is interpreted.
IRLAM brings these elements together through a wavelength-selective Quantum Cascade Laser, a compact multi-pass Herriott Cell and a feature-based concentration calculation algorithm. The QCL targets an appropriate absorption feature, the Herriott Cell extends the optical path and the calculation method extracts the information needed to determine concentration and correct for interference.
By integrating these technologies, IRLAM supports sensitive, rapid gas analysis for vehicle and engine development. Its architecture enables direct NO and NO2 measurement, wet exhaust analysis and reduced dependence on converter-related components across laboratory and on-road measurement environments.
About the Original Author:
Joshua Israel, Applications Engineering and Technical Marketing Manager, HORIBA Instruments, Inc.
Read the SAE technical paper comparing IRLAM and conventional CLD measurements using certification-quality NOx data from diluted light-duty vehicle exhaust.
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