MUMBAI, India, Sept. 28 -- Intellectual Property India has published a patent application (202611099838 A) filed by D. K. Tiwari on August 18, 2026, for Internal Combustion Engine Test Machine.
Inventor includes D. K. Tiwari.
The application for the patent was published on September 25, 2026, under issue no. 39/2026.
Abstract: [505] The advanced internal combustion engine test machine introduces an innovative multi-purpose diagnostic framework for comprehensive engine performance evaluation that integrates computational validation protocols with adaptive parameter determination mechanisms, facilitating real-time performance calculations, dynamic load optimization, and robust operational confirmation while maintaining seamless industrial integration and testing accuracy for consistent engine applications. [510] The comprehensive engine testing framework employs adaptive mathematical algorithms and intuitive diagnostic protocols, utilizing embedded computational processing arrays and energy-efficient sensor systems to ensure timely fault identification, enhanced performance understanding, and optimal operational reliability while maintaining continuous parameter monitoring capabilities. [515] The integrated methodology combines multi-dimensional performance techniques with artificial intelligence-driven pattern recognition systems, leveraging variable-precision sensor signals and multi-factor diagnostic indicators to optimize testing procedures and calculation workflows for maximum measurement accuracy and minimal diagnostic uncertainty during critical industrial applications. [520] The novel responsive test architecture features engineered high-precision sensor components with specialized engine fingerprinting protocols, enabling complex multi-stage performance verification while ensuring measurement consistency and performance optimization across various engine test benches without compromising system reliability. [525] The innovative design incorporates strategic validation mechanisms for enhanced fault identification and operational security, utilizing optimized multi-function systems and adaptive diagnostic technology to ensure legitimate engine assessment while maintaining functionality across diverse industrial environments and testing scenarios. [530] Implementation methodology emphasizes scalable diagnostic integration and efficient testing sequences, implementing interactive measurement measures and pattern recognition algorithms to achieve superior parameter determination, enhanced fault identification, and unauthorized data manipulation prevention while ensuring technological simplicity during industrial monitoring. [535] The system demonstrates exceptional adaptability through comprehensive integration of engine identification protocols and intelligent diagnostic technologies, validating its effectiveness across various multifunctional test configurations and industrial scenarios while maintaining consistent measurement performance and operational efficiency under diverse conditions. [540] The developed framework enables sustainable and reliable testing of internal combustion engines through streamlined, AI-powered diagnostic systems, providing significant advantages over traditional test-bench approaches through variable validation mechanisms, adaptive identification protocols, and improved parameter assignment while maintaining superior measurement accuracy during critical industrial testing procedures.
Disclaimer: Curated by HT Syndication.
