scholarly journals Costate Estimation of PMP-Based Control Strategy for PHEV Using Legendre Pseudospectral Method

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Hanbing Wei ◽  
Yao Chen ◽  
Zhiyuan Peng
Keyword(s):  
Control Strategy ◽  
Pseudospectral Method ◽  
Jump Condition ◽  
Condition Estimation ◽  
Optimal Value ◽  
Equivalent Fuel ◽  
Driving Condition ◽  
Global Optimal ◽  
Legendre Pseudospectral Method ◽  
Equivalent Fuel Consumption

Costate value plays a significant role in the application of PMP-based control strategy for PHEV. It is critical for terminal SOC of battery at destination and corresponding equivalent fuel consumption. However, it is not convenient to choose the approximate costate in real driving condition. In the paper, the optimal control problem of PHEV based on PMP has been converted to nonlinear programming problem. By means of KKT condition costate can be approximated as KKT multipliers of NLP divided by the LGL weights. A kind of general costate estimation approach is proposed for predefined driving condition in this way. Dynamic model has been established in Matlab/Simulink in order to prove the effectiveness of the method. Simulation results demonstrate that the method presented in the paper can deduce the closer value of global optimal value than constant initial costate value. This approach can be used for initial costate and jump condition estimation of PMP-based control strategy for PHEV.

Equivalent fuel consumption optimal control of a series hybrid electric vehicle

2009 ◽  
Vol 223 (8) ◽  
pp. 1003-1018 ◽  
Author(s):  
J-P Gao ◽  
G-M G Zhu ◽  
E G Strangas ◽  
F-C Sun
Keyword(s):  
Optimal Control ◽  
Fuel Consumption ◽  
Control Strategy ◽  
Supervisory Control ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Optimal Control Strategy ◽  
Equivalent Fuel ◽  
Hybrid Electric ◽  
Equivalent Fuel Consumption

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.

scholarly journals Energy Control Strategy for Parallel Hybrid Electric Vehicle Based on Terminal Neural Network

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Haitao Yan ◽  
Yongzhi Xu
Keyword(s):  
Neural Network ◽  
Fuel Consumption ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Energy Control ◽  
Time Performance ◽  
Equivalent Fuel ◽  
Hybrid Electric ◽  
Equivalent Fuel Consumption

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.

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
Keyword(s):  
Fuel Consumption ◽  
Penalty Function ◽  
Control Strategy ◽  
Regenerative Braking ◽  
Optimization Of Parameters ◽  
Equivalent Fuel ◽  
Equivalent Fuel Consumption ◽  
Orthogonal Optimization ◽  
Consumption Control ◽  
Precise Expression

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.

scholarly journals Design and Validation of Real-Time Optimal Control with ECMS to Minimize Energy Consumption for Parallel Hybrid Electric Vehicles

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Aiyun Gao ◽  
Xiaozhong Deng ◽  
Mingzhu Zhang ◽  
Zhumu Fu
Keyword(s):  
Optimal Control ◽  
Real Time ◽  
Control Strategy ◽  
Hybrid Electric Vehicles ◽  
Time Optimal Control ◽  
Parallel Hybrid ◽  
Equivalent Fuel ◽  
Time Optimal ◽  
Equivalent Factor ◽  
Equivalent Fuel Consumption

A real-time optimal control of parallel hybrid electric vehicles (PHEVs) with the equivalent consumption minimization strategy (ECMS) is presented in this paper, whose purpose is to achieve the total equivalent fuel consumption minimization and to maintain the battery state of charge (SOC) within its operation range at all times simultaneously. Vehicle and assembly models of PHEVs are established, which provide the foundation for the following calculations. The ECMS is described in detail, in which an instantaneous cost function including the fuel energy and the electrical energy is proposed, whose emphasis is the computation of the equivalent factor. The real-time optimal control strategy is designed through regarding the minimum of the total equivalent fuel consumption as the control objective and the torque split factor as the control variable. The validation of the control strategy proposed is demonstrated both in the MATLAB/Simulink/Advisor environment and under actual transportation conditions by comparing the fuel economy, the charge sustainability, and parts performance with other three control strategies under different driving cycles including standard, actual, and real-time road conditions. Through numerical simulations and real vehicle tests, the accuracy of the approach used for the evaluation of the equivalent factor is confirmed, and the potential of the proposed control strategy in terms of fuel economy and keeping the deviations ofSOCat a low level is illustrated.

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