Page 105 - IJEEE-2022-Vol18-ISSUE-1
P. 105
Al-Flehawee & Al-Mayyahi | 101
and SOC as well as focus and attention to obtain the best value. Although this strategy makes many calculations, it
possible minimization in fuel consumption. was able to implement all the optimization tasks required of
it well due to its ability to find the optimal operating points
Fig.7: The trajectories of the optimal manipulated variables for energy converters in this vehicle. It is possible to benefit
It is noted that the tracking and dynamic response of the from this study by comparing the NMPC control strategy
with other energy management strategies for the same
reference speed of the series-parallel HEV is good as shown vehicle, in addition to the possibility of using the
in Fig.8, where the series-parallel HEV model was able to mathematical model equations for this vehicle in other
travel 10.9 km and the total fuel used was 0.4482 liters during studies.
the New European Driving Cycle (NEDC), and it is
considered a good result in terms of improving fuel CONFLICT OF INTEREST
consumption. In the end, it can be said that a model of the
hybrid electric vehicle was able to achieve the objectives The authors have no conflict of relevant interest to this
required of it. article.
Fig.8: Series-parallel HEV speed by using NMPC strategy REFERENCES
VIII. CONCLUSIONS [1] M.-K. Tran, M. Akinsanya, S. Panchal, R. Fraser, and
To implement the NMPC control strategy for power M. Fowler, “Design of a Hybrid Electric Vehicle
management among the hybrid electric vehicle's energy Powertrain for Performance Optimization Considering
converters, the nonlinear optimization problem must first be Various Powertrain Components and Configurations,”
appropriately created, which includes the cost function Vehicles, vol. 3, no. 1, pp. 20–32, 2020, doi:
subject to the physical constraints of the vehicle and the 10.3390/vehicles3010002.
mathematical prediction model that is used to evaluate the [2] S. B. Kanap, “Modeling and Simulation with Optimal
vehicle's future behavior based on the vehicle's current Gear Ratio for a Forward- Looking , Velocity-Driven ,
measurements which are state variables and control inputs. Power-Split Hybrid Electric Vehicle,” Western Michigan
In this study, this strategy improved the fuel consumption University, 2019.
and dynamic performance of the vehicle as well as [3] S. Borthakur and S. C. Subramanian, “Optimized
maintained the state of charge (SOC) of the battery at the Design and Analysis of a Series-Parallel Hybrid Electric
desired value, they are formulated in the cost function. Vehicle Powertrain for a Heavy Duty Truck,” IFAC-
Secondly, this strategy solves the constrained nonlinear PapersOnLine, vol. 51, no. 1, pp. 184–189, 2018, doi:
optimization problem by using the SQP algorithm at each 10.1016/j.ifacol.2018.05.034.
sampling step to find the optimum values torque of the [4] J. P. Torreglosa, P. Garcia-Triviño, D. Vera, and D. A.
engine, motor, and generator to provide the power required López-García, “Analyzing the improvements of energy
to drive the vehicle. This strategy was able to achieve the management systems for hybrid electric vehicles using a
required objectives of making the vehicle go at the required systematic literature review: How far are these controls
speed with the best fuel consumption, in addition to making from rule-based controls used in commercial vehicles?,”
the value of the state of the charge of the battery at the desired Appl. Sci., vol. 10, no. 23, pp. 1–25, 2020.
value. This indicates that the strategy was able to supply the [5] Y. Hu, W. Li, K. Xu, T. Zahid, F. Qin, and C. Li,
motor with electrical energy, either the generator or the “Energy management strategy for a hybrid electric vehicle
kinetic energy captured from the deceleration of the vehicle based on deep reinforcement learning,” Appl. Sci., vol. 8,
so that the state of the charge remains close to the desired no. 2, 2018, doi: 10.3390/app8020187.
[6] A. M. Ali and D. Söffker, “Towards optimal power
management of hybrid electric vehicles in real-time: A
review on methods, challenges, and state-of-the-art
solutions,” Energies, vol. 11, no. 3, pp. 1–24, 2018, doi:
10.3390/en11030476.
[7] J. Hu, X. Jiang, and L. Zheng, “Design and analysis of
hybrid electric vehicle powertrain configurations
considering energy transformation,” Int. J. Energy Res.,
vol. 42, no. 15, pp. 4719–4729, 2018, doi: 10.1002/er.4225.
[8] J. Yang and G. G. Zhu, “Model predictive control of a
power split hybrid powertrain,” in 2016 American Control
Conference (ACC), 2016, vol. 2016-July, pp. 617-622.
IEEE.
[9] H. A. Borhan, A. Vahidi, A. M. Phillips, M. L. Kuang,
and I. V. Kolmanovsky, “Predictive energy management of
a power-split hybrid electric vehicle,” 2009 Am. Control
Conf., pp. 3970-3976. IEEE, 2009.
[10] P. Poramapojana and B. Chen, “Minimizing HEV fuel
