Abstract
In this paper, we propose a new control logic for hybrid vehicle control technology using predictable real road information. The newly proposed control logic is implemented in real time by applying the shifting map of the engine and transmission applied to the hybrid vehicle and the mode conversion map extracted from various driving modes. The proposed control logic has the advantage of minimizing the loss compared to the theoretical maximum fuel consumption implemented in the backward simulation and achieving more stable shifting and mode conversion. As a result of applying the proposed control algorithm to the omnidirectional simulation, the result showed better fuel efficiency improvement than the existing rule base control method. The newly proposed control algorithm can be used as a hybrid control algorithm that can solve the computation time problems required for the optimization process through the conventional reverse simulation and can perform stable shift and mode conversion in real time.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Abbreviations
- ṁ fc :
-
instantaneous fuel consumption (g/s)
- T eng :
-
engine torque (Nm)
- ω eng :
-
engine speed (rad/s)
- P motelec :
-
electric power of battery (W)
- T mot :
-
motor torque (Nm)
- ω mot :
-
motor speed (rad/s)
- F load :
-
road road (N)
- m v :
-
mass of vehicle (kg)
- a v :
-
accelearation of vehicel (m/s2)
- C r :
-
coefficient of rolling resistance
- ρ a :
-
air density (kg/m3)
- A f :
-
frontal area of vehicle (m2)
- Cd:
-
coefficient of aero dynamic drag (−)
- V v :
-
velocity of vehicle (m/s)
- r tire :
-
tire radius (m)
- P eng :
-
engine power (kw)
- P mot :
-
motor power (kw)
- ω in :
-
speed of input shaft (rad/s)
- ω out :
-
speed of output shaft (rad/s)
- F TM :
-
gear ratio of final drive (−)
- Q bat :
-
capacity of battery (Ah)
- V bat :
-
open circuit voltage of battery (V)
- R bat :
-
internal resistance (Ω)
- P bat :
-
output power of battery (W)
- S:
-
time (sec)
- DP:
-
dynamic programing
- HCU:
-
hybrid control unit
- PSR:
-
power split ratio
- G:
-
gravity (m/s2)
References
Kim, B., Kim, Y.-G., Kim, T., Park, Y.-I. and Cha, S. W. (2009). HEV cruise control strategy on GPS (Navigation) information. World Electric Vehicle J., 3, 589–596.
Kim, G., Park, Y., Ro, Y. and Jung, J. (2016). Components sizing of powertrain for a parallel hybridization of the mid-size low-floor buses. J. Korea Academia-Industrial Cooperation Society17, 8, 582–594.
Kim, N., Lee, D., Yang, S., Park, Y. and Cha, S. (2008). Optimization for analyzing fuel consumption of HEVs. KSAE 30th Anniversary Conf. Proc., Korean Society of Automotive Engineers, 2042–2047.
Lee, H., Jeong, J., Park, Y. and Cha, S. W. (2017). Energy management strategy of hybrid electric vehicle using battery state of charge trajectory information. Int. J. Precision Engineering and Manufacturing-Green Technology4, 1, 79–86.
Min, B., Park, T., Kim, I., Suh, B. J., Lee, J. and Kim, S. (2011). Development of fuel economy improvement technique for hybrid electric vehicle by using driving condition prediction. KSAE Annual Conf. Proc., Korean Society of Automotive Engineers, 2749–2754.
Acknowledgement
This study was supported by the Research Program funded by the SeoulTech (Seoul National University of Science and Technology).
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Lim, S.H., Kim, J. & Park, Y.I. Real-Time Control Algorithm for Hybrid System Using Gear Shift Map and Mode Conversion Map. Int.J Automot. Technol. 21, 41–49 (2020). https://doi.org/10.1007/s12239-020-0005-z
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12239-020-0005-z