A team of scientists led by Professor Yongkang Dong from the National Key Laboratory of Laser Spatial Information at Harbin Institute of Technology, China, has developed a multifunctional frequency modulated continuous wave (FMCW) LiDAR system that can perform high-precision 3D imaging and multi-parameter sensing simultaneously. This innovation addresses the growing need for integrated perception systems in new energy vehicles and autonomous driving technologies, where safety and efficiency are paramount.
Traditional FMCW LiDAR systems provide excellent 3D imaging capabilities but are limited to measuring distance and velocity. They cannot detect internal battery states or environmental parameters, which are critical for preventing thermal runaway in electric vehicle batteries. Thermal runaway is a major safety concern, and early warning depends on monitoring multiple parameters such as temperature, electrolyte density, and characteristic gases. Currently, these functions are handled by separate systems, increasing complexity, cost, and integration challenges. The proposed multifunctional LiDAR aims to consolidate these functions into a single device.
The new system works by detecting echo signals from both free space and optical fiber, enabling 3D imaging and simultaneous measurement of various physical parameters. In proof-of-concept experiments, the researchers successfully imaged a target at 30 meters with adjustable resolution from 0.3 cm to 1.2 cm. They also measured the electrolyte density and temperature of a battery with accuracies of 3×10⁻⁵ g/mL and 0.5 °C, respectively. Additionally, the system detected concentrations of gases such as C2H2, CO2, and CH4, which are critical for monitoring thermal runaway, with detection limits of 0.07 ppm, 48 ppm, and 0.56 ppm, respectively.
The technology leverages optical frequency domain reflectometry (OFDR), which extends FMCW LiDAR principles into optical fibers. OFDR uses a linearly modulated continuous light source for fiber measurements, offering high spatial resolution and a large dynamic range. This approach allows the system to demodulate reflection spectra from fiber Bragg gratings (FBG), Fabry-Perot (FP) cavities, and multi-pass cells (MPC) to extract temperature, gas concentration, and liquid density data.
The multifunctional LiDAR system holds significant potential for applications in new energy vehicles and spacecraft. By integrating imaging and sensing into one demodulator, it could provide a streamlined solution to enhance vehicle safety. The researchers envision that this technology could become a key component in the next generation of autonomous driving systems, offering a cost-effective and compact alternative to current multi-system setups.
For more details, the full research paper is published in Light: Science & Applications with DOI: 10.37188/lam.2026.102.
