GPS Coordinates Based Route Recognition and Predictive Functions 2022-28-0124

Historically, whenever the automotive solutions’ state of art reaches a saturation level, the integration of new verticals of technology has always raised new opportunities to innovate, enhance and optimize automotive solutions. The predictive powertrain solutions using connectivity elements (e.g., navigation unit, e-Horizon or cloud-based services) are one of such areas of huge interest in automotive industry. The prior knowledge of trip destination and its route characteristics has potential to make prediction of powertrain modes or events in certain order and therefore it can add value in various application areas such as optimized energy management, lower fuel consumption, superior safety and comfort, etc. However, when it comes to a point of commercializing such real applications with predictive function solutions, there could be various challenges such as micro-controller limitations, connectivity infrastructure limitations in varied geographical locations, cost sensitivity in emerging markets, unavailability of services like e-Horizon, etc. In order to address these practical challenges, GPS coordinates-based route recognition method is developed which is not only optimized for embedded applications in electronic control units (ECU) with limited memory, but also easily viable for emerging market locations. Additionally, the method also learns and recognizes the route without destination knowledge reinforced by driver, considering the fact that for regular routes, driver does not enter destination or even does not switch on navigation unit at all.

Furthermore, two of the real-time powertrain applications based on the route recognition are demonstrated. One is, predictive DPF regeneration and another is predictive diagnosis of exhaust components, both aiming to improve the performance of emission control system. To demonstrate that GPS coordinates-based route recognition is comparable and can act as supplement to e-Horizon service-based route prediction in emerging markets, the predictive DPF regeneration application with both approaches is studied.