Study of the Minimization of Instantaneous Equivalent Fuel Consumption Control Strategy of HEV

2012 ◽  
Vol 462 ◽  
pp. 669-675 ◽  
Author(s):  
Peng Yu Wang ◽  
Qing Nian Wang ◽  
Zhi Xuan Li ◽  
Qing Lin Zhu

A control strategy which based on minimum instantaneous equivalent fuel consumption was proposed in this paper. The important parameters that affected the calculation of instantaneous fuel consumption were analyzed. The important parameters include battery equivalent fuel consumption, penalty function to maintain the battery SOC and the revise of the regenerative braking energy. More precise expression of minimum instantaneous fuel consumption was deduced. Under the simulation platform of ADVISOR software, orthogonal optimization of parameters was performed and the range of important parameters in the optimization of expression was determined.

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 2021 ◽  
pp. 1-9
Author(s):  
Haitao Yan ◽  
Yongzhi Xu

Energy control strategy is a key technology of hybrid electric vehicle, and its control effect directly affects the overall performance of the vehicle. The current control strategy has some shortcomings such as poor adaptability and poor real-time performance. Therefore, a transient energy control strategy based on terminal neural network is proposed. Firstly, based on the definition of instantaneous control strategy, the equivalent fuel consumption of power battery was calculated, and the objective function of the minimum instantaneous equivalent fuel consumption control strategy was established. Then, for solving the time-varying nonlinear equations used to control the torque output, a terminal recursive neural network calculation method using BARRIER functions is designed. The convergence characteristic is analyzed according to the activation function graph, and then the stability of the model is analyzed and the time efficiency of the error converging to zero is deduced. Using ADVISOR software, the hybrid power system model is simulated under two typical operating conditions. Simulation results show that the hybrid electric vehicle using the proposed instantaneous energy control strategy can not only ensure fuel economy but also shorten the control reaction time and effectively improve the real-time performance.


2015 ◽  
Vol 9 (1) ◽  
pp. 181-188 ◽  
Author(s):  
Xu Miao ◽  
Zhao Dingxuan ◽  
Ni Tao ◽  
Wang Yao

Hybrid excavator control strategy based on rules optimizes the specific fuel consumption only to determine engine operating point in the perspective of qualitative analysis, it is not sufficient to reduce the excavator fuel consumption because of ignoring the affect of engine power output. In this paper, an instantaneous minimum fuel consumption control strategy for hybrid power-train is proposed, strategy determines the ideal operating point taking both the main influence factors of fuel consumption into consideration, the ultra-capacitor energy variation which is caused by the motor power output is converted to the equivalent fuel consumption and included in the current power-train fuel consumption. The output torque combination of the engine and motor which minimize the current fuel consumption is adopted. The bench test results validate that the engine is 12% fuel saving on average after optimizing, and at the same time the ultra-capacitor energy is effectively maintained.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Wei Wang ◽  
Zhenjiang Cai ◽  
Shaofei Liu

A real-time control is proposed for plug-in-hybrid electric vehicles (PHEVs) based on dynamic programming (DP) and equivalent fuel consumption minimization strategy (ECMS) in this study. Firstly, the resulting controls of mode selection and series mode are stored in tables through offline simulation of DP, and the parallel HEV mode uses ECMS-based real-time algorithm to reduce the application of maps and avoid manual adjustment of parameters. Secondly, the feedback energy management system (FMES) is built based on feedback from SoC, which takes into account the charge and discharge reaction (CDR) of the battery, and in order to make full use of the energy stored in the battery, the reference SoC is introduced. Finally, a comparative simulation on the proposed real-time controller is conducted against DP, the results show that the controller has a good performance, and the fuel consumption value of the real-time controller is close to the value using DP. The engine operating conditions are concentrated in the low fuel consumption area of the engine, and when the driving distance is known, the SoC can follow the reference SoC well to make full use of the energy stored in the battery.


Sign in / Sign up

Export Citation Format

Share Document