Abstract
The stringent fuel consumption and pollutants reduction standards enforce manufacturers and carmakers to have a closer look on new powertrain architectures for individual vehicles. In that context, studies on hybrid vehicles appear today in a substantial scale. The association of a high efficiency electrical motor with an internal combustion engine needs specific control laws in order to optimize the energy management.
This paper presents a new control strategy developed by SiemensVDO Automotive and the LEEI laboratory on an electrical parallel hybrid vehicle. A supervisor is built to have a full control of the drive train (clutch, gearshifts, thermal IC engine torque and electrical motor torque) to improve fuel consumption and to maintain an admissible battery state of charge. The optimization algorithm is realized on the overall trip. An offline global optimization is made to analyze the main optimal behavior of the system. The results of that analysis are associated to an onboard navigation system that provides information on the vehicle environment, traffic, distance and road type between the starting point and the destination of the planned trip. Such information is used to analyze the different phases of the trip and to determine a vehicle speed profile and torque needs during the trip, for a better battery management with larger electrical motor torque possibilities. It will also provide optimal gear ratio that can be applied knowing the future acceleration constrains. This includes the concept of driveability in our criterion that is often in contradiction with energy savings.
It is clear that this strategy is not intended to calculate the global optimal solution. But we hope to obtain greater reduction of fuel consumption by adding trip prediction to the supervision system, instead of an offline tuning of mapped working points.
The study is supported by the French public agency ADEME (Agence De lEnvironnement et Maîtrise de lEnergie (Environment and Energy Management Agency).