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The pressure of stringent emission norms and the need for reducing CO2 footprint has made Hybrid technology the need of future mobility. The viability of Hybrid heavily depends on the fuel economy margin it offers over the conventional powertrain. The advent of intelligent powertrain control strategies and optimization possibilities in the conventional powertrain arena tends to decrease the gap between the hybrid and conventional fuel economy. To retain the same fuel economy advantage over the intelligent conventional powertrain, hybrids need to have innovative and intelligent control strategies that optimize the energy balance between the ICE and E-machine without compromising the drivability and performance aspects of the vehicle. This paper explains an intelligent predictive control strategy for High Voltage Battery State of Charge of the parallel hybrid systems.

In the era where governmental agencies are perennially pushing automobile OEMs for reducing harmful emissions and customers looking for vehicles with better fuel economy values, it is imperative on the manufacturers to implement new technologies to appease them. Of the many new technologies, the most promising ones are the new control strategies/algorithms which predictively access the road condition, weather, traffic situations and help automobile to function in the most efficient mode. These control strategies/algorithms are termed as “Predictive technologies”. The most common way to assess the benefit of such new technologies is to simulate the vehicle behavior in conjunction with the existing complex control strategies of Hybrid vehicles in simulation environment.

Availability of road navigation data and route pattern details to the vehicle controller allows the use of predictive algorithms to obtain optimal performance from the vehicle. Conventionally, in the automated transmissions, gear position values are decided from predefined maps depending on the load demand and vehicle velocity at that instant. Due to the instantaneous decisions taken to get the gear position, minor changes in terrain sometimes might cause multiple unwanted gear shifts. The paper presents the concept of predictive optimal gear shifting strategy, utilizing the route information from the vehicle navigation system and vehicle state. Route terrain information is processed to analyze the vehicle behavior at future route gradient segments. Several categories of vehicle behavior are identified and at each decision point, the driving state is classified into one of these categories.