Estimating Tire Particulate Emissions via Driving Correlations

The patent uses a sensor system that measures driving operation values (such as acceleration, braking, steering angle) and creates a copy or model of particulate emissions behavior through correlation algorithms stored in the control unit. Instead of directly measuring particulate matter at each tire, the system copies the emissions pattern based on measurable driving parameters, thereby avoiding the need for multiple expensive particulate matter sensors while still achieving accurate emissions estimation

The patent replaces the mechanical/physical particulate matter sensors with an electronic sensor system that measures driving operation values combined with computational algorithms. The control unit processes driving operation data through stored correlations to estimate particulate emissions, substituting direct physical measurement with an electronic-computational approach that is less complex and more cost-effective

The patent makes the existing sensor system and control unit perform multiple functions: they not only monitor driving operation for vehicle control purposes but also simultaneously estimate particulate emissions from tire abrasion. The same sensors that track acceleration, braking, and steering are reused for emissions measurement, eliminating the need for separate dedicated particulate matter sensors and reducing manufacturing costs

The system creates a computational model (copy) of particulate emissions behavior by correlating driving operation values with pre-stored emission patterns. This copying approach allows complete emissions monitoring across all tires using a single integrated system rather than requiring multiple physical sensors, thereby reducing manufacturing costs while maintaining measurement completeness