scholarly journals Real-time control algorithm for minimising energy consumption in parallel hybrid electric vehicles

2020 ◽  
Vol 10 (4) ◽  
pp. 331-340
Author(s):  
Bo Zhang ◽  
Fuguo Xu ◽  
Jiangyan Zhang ◽  
Tielong Shen
Keyword(s):  
Energy Consumption ◽  
Real Time ◽  
Electric Vehicles ◽  
Control Algorithm ◽  
Hybrid Electric Vehicles ◽  
Real Time Control ◽  
Time Control ◽  
Parallel Hybrid ◽  
Hybrid Electric

Optimal control of fuel economy in parallel hybrid electric vehicles

2007 ◽  
Vol 221 (9) ◽  
pp. 1097-1106 ◽  
Author(s):  
J Pu ◽  
C Yin
Keyword(s):  
Optimal Control ◽  
Real Time ◽  
Electric Vehicles ◽  
Fuel Economy ◽  
Hybrid Electric Vehicles ◽  
Real Time Control ◽  
Simulation Code ◽  
Computation Efficiency ◽  
Parallel Hybrid ◽  
Hybrid Electric

A mathematical model of optimal control of fuel economy for parallel hybrid electric vehicles (HEVs) and its dynamic programming (DP) recursive equation and numerical DP algorithm are presented. The effect of frequent gear shifting and engine stop-starting on drivability and fuel economy are both taken into account in the cost function. To overcome the curse of dimensionality of numerical DP, an algorithm restricting the exploring region is proposed to reduce largely the computational complexity, and the quantization increments are carefully selected to balance computation accuracy and efficiency. Furthermore, instead of being simplified, the system model is converted into a real-time simulation code by using MATLAB/RTW to improve the computation efficiency. Finally, a case study is presented. The vehicle testing results, the simulation results, and the DP results are compared and analysed, indicating that the maximum performance and the optimal control policy of the HEV can be determined by the algorithm proposed in this paper within an acceptable time and that the results can be used to evaluate and improve the real-time control strategy.

scholarly journals Real-Time Energy Management of Parallel Hybrid Electric Vehicles Using Linear Quadratic Regulation

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5538
Author(s):  
Bảo-Huy Nguyễn ◽  
João Pedro F. Trovão ◽  
Ronan German ◽  
Alain Bouscayrol
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Engine Fuel ◽  
Linear Quadratic ◽  
Loop Control ◽  
Parallel Hybrid ◽  
Linear Quadratic Regulation ◽  
Hybrid Electric

Optimization-based methods are of interest for developing energy management strategies due to their high performance for hybrid electric vehicles. However, these methods are often complicated and may require strong computational efforts, which can prevent them from real-world applications. This paper proposes a novel real-time optimization-based torque distribution strategy for a parallel hybrid truck. The strategy aims to minimize the engine fuel consumption while ensuring battery charge-sustaining by using linear quadratic regulation in a closed-loop control scheme. Furthermore, by reformulating the problem, the obtained strategy does not require the information of the engine efficiency map like the previous works in literature. The obtained strategy is simple, straightforward, and therefore easy to be implemented in real-time platforms. The proposed method is evaluated via simulation by comparison to dynamic programming as a benchmark. Furthermore, the real-time ability of the proposed strategy is experimentally validated by using power hardware-in-the-loop simulation.

scholarly journals A Novel Control Algorithm Design for Hybrid Electric Vehicles Considering Energy Consumption and Emission Performance

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2698 ◽  
Author(s):  
Yuan Qiao ◽  
Yizhou Song ◽  
Kaisheng Huang
Keyword(s):  
Energy Consumption ◽  
Objective Function ◽  
Electric Vehicles ◽  
Control Algorithm ◽  
Hybrid Electric Vehicles ◽  
Algorithm Design ◽  
Classical Dynamic ◽  
Emission Performance ◽  
Simulation Results ◽  
Hybrid Electric

Under the severe challenge of increasingly stringent emission regulations and constantly improving fuel economy requirements, hybrid electric vehicles (HEVs) have attracted widespread attention in the auto industry as a practicable technical route of green vehicles. To address the considerations on energy consumption and emission performance simultaneously, a novel control algorithm design is proposed for the energy management system (EMS) of HEVs. First, energy consumption of the investigated P3 HEV powertrain is determined based on bench test data. Second, crucial performance indicators of NOx and particle emissions, prior to a catalytic converter, are also measured and processed as a prerequisite. A comprehensive objective function is established on the grounds of the Equivalent Consumption Minimization Strategy (ECMS) and corresponding simulation models are constructed in MATLAB/SIMULINK. Subsequently, the control algorithm is validated against the simulation results predicated on the Worldwide-Harmonized Light-Vehicle Test Procedure (WLTP).Integrated research contents include: (1) The searching process aimed at the optimal solution of the pre-established multi-parameter objective function is thoroughly investigated; (2) the impacts of weighting coefficients pertaining to two exhaust pollutants upon the specific configurations of the proposed control algorithm are discussed in detail; and (3) the comparison analysis of the simulation results obtained from ECMS and classical Dynamic Programming (DP), respectively, is performed.

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