scholarly journals Optimal Energy Control Strategy Design for a Hybrid Electric Vehicle

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Yuan Zou ◽  
Hou Shi-jie ◽  
Li Dong-ge ◽  
Gao Wei ◽  
Xiao-song Hu

A heavy-duty parallel hybrid electric truck is modeled, and its optimal energy control is studied in this paper. The fundamental architecture of the parallel hybrid electric truck is modeled feed-forwardly, together with necessary dynamic features of subsystem or components. Dynamic programming (DP) technique is adopted to find the optimal control strategy including the gear-shifting sequence and the power split between the engine and the motor subject to a battery SOC-sustaining constraint. Improved control rules are extracted from the DP-based control solution, forming near-optimal control strategies. Simulation results demonstrate that a significant improvement on the fuel economy can be achieved in the heavy-duty vehicle cycle from the natural driving statistics.

Author(s):  
J-P Gao ◽  
G-M G Zhu ◽  
E G Strangas ◽  
F-C Sun

Improvements in hybrid electric vehicle fuel economy with reduced emissions strongly depend on their supervisory control strategy. In order to develop an efficient real-time supervisory control strategy for a series hybrid electric bus, the proposed equivalent fuel consumption optimal control strategy is compared with two popular strategies, thermostat and power follower, using backward simulations in ADVISOR. For given driving cycles, global optimal solutions were also obtained using dynamic programming to provide an optimization target for comparison purposes. Comparison simulations showed that the thermostat control strategy optimizes the operation of the internal combustion engine and the power follower control strategy minimizes the battery charging and discharging operations which, hence, reduces battery power loss and extends the battery life. The equivalent fuel consumption optimal control strategy proposed in this paper provides an overall system optimization between the internal combustion engine and battery efficiencies, leading to the best fuel economy.


2021 ◽  
Vol 12 (2) ◽  
pp. 85
Author(s):  
Ying Tian ◽  
Jiaqi Liu ◽  
Qiangqiang Yao ◽  
Kai Liu

In this paper, the dynamic programming algorithm is applied to the control strategy design of parallel hybrid electric vehicles. Based on MATLAB/Simulink software, the key component model and controller model of the parallel hybrid system are established, and an offline simulation platform is built. Based on the platform, the global optimal control strategy based on the dynamic programming algorithm is studied. The torque distribution rules and shifting rules are analyzed, and the optimal control strategy is adopted to design the control strategy, which effectively improves the fuel economy of plug-in hybrid electric vehicles. The fuel consumption rate of this parallel hybrid electric vehicle is based on china city bus cycle (CCBC) condition.


2013 ◽  
Vol 753-755 ◽  
pp. 1659-1664
Author(s):  
Jun Yan

To reduce the fuel consumption and exhaust (HC, CO) emissions of parallel hybrid electric vehicle, the control strategy of the hybrid electric vehicle is studied in this paper. First it briefly analyzes the structure and working principle of the parallel hybrid electric vehicle drive system. Then a cost function is proposed which explains the fuel consumption and emissions. According to the minimum principle the minimum of the cost function can be got, consequently, the optimal control strategy can be obtained. Furthermore, in order to verify the effectiveness of the optimal control strategy, in MATLAB environment, it establishes a dynamic simulation model for hybrid electric vehicles. Through a comparative study between the optimal control strategy on and the traditional rules control strategy, the results of experiment it reveals that the optimal control strategy can effectively reduces fuel consumption and emissions of hybrid electric vehicles.


Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1833
Author(s):  
Waruna Maddumage ◽  
Malika Perera ◽  
Rahula Attalage ◽  
Patrick Kelly

Millions of three-wheelers in large cities of Asia and Africa contribute to the already increasing urban air pollutants. An emerging method to reduce adverse effects of the growing three-wheeler fleet is hybrid-electric technology. The overall efficiency of a hybrid electric vehicle heavily depends on the power management strategy used in controlling the main powertrain components of the vehicle. Recent studies highlight the need for a comprehensive report on developing an easy-to-implement and efficient control strategy for hybrid electric three-wheelers. Thus, in the present study, a design methodology for a rule-based supervisory controller of a pre-transmission parallel hybrid three-wheeler based on an optimal control strategy (i.e., dynamic programming) is proposed. The optimal control problem for minimizing fuel, emissions (i.e., HC, CO and NOx) and gear shift frequency are solved using dynamic programming (DP). Numerical issues of DP are analyzed and trade-offs between optimizing objectives are presented. Since DP strategy cannot be implemented as a real-time controller, useful strategies are extracted to develop the proposed rule-based strategy. The developed rule-based strategy show performance within 10% of the DP results on WLTC and UDC-NEDC drive cycles and has the clear advantage of being near-optimal, easy-to-implement and computationally less demanding.


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