scholarly journals An Optimized Energy Management Strategy of 48V Mild Hybrid Electrical Vehicle to Reduce Fuel Consumption

2017 ◽  
Author(s):  
Luyao Zeng ◽  
Zhiguo Zhao
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Management Strategy ◽  
Reduce Fuel Consumption ◽  
Energy Management Strategy ◽  
Electrical Vehicle ◽  
Mild Hybrid ◽  
Hybrid Electrical Vehicle

scholarly journals Adaptive Rule-Based Energy Management Strategy for a Parallel HEV

Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4472 ◽  
Author(s):  
Rishikesh Mahesh Bagwe ◽  
Andy Byerly ◽  
Euzeli Cipriano dos Santos ◽  
Ben-Miled
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Duty Cycle ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Detailed Knowledge ◽  
Energy Management Strategy ◽  
Rule Based ◽  
Engine Efficiency ◽  
Efficiency Map

This paper proposes an Adaptive Rule-Based Energy Management Strategy (ARBS EMS) for a parallel hybrid electric vehicle (HEV). The aim of the strategy is to facilitate the aftermarket hybridization of medium- and heavy-duty vehicles. ARBS can be deployed online to optimize fuel consumption without any detailed knowledge of the engine efficiency map of the vehicle or the entire duty cycle. The proposed strategy improves upon the established Preliminary Rule-Based Strategy (PRBS), which has been adopted in commercial vehicles, by dynamically adjusting the regions of operations of the engine and the motor. It prevents the engine from operating in highly inefficient regions while reducing the total equivalent fuel consumption of the vehicle. Using an HEV model developed in Simulink®, both the proposed ARBS and the established PRBS strategies are compared over an extended duty cycle consisting of both urban and highway segments. The results show that ARBS can achieve high MPGe with different thresholds for the boundary between the motor region and the engine region. In contrast, PRBS can achieve high MPGe only if this boundary is carefully established from the engine efficiency map. This difference between the two strategies makes the ARBS particularly suitable for aftermarket hybridization where full knowledge of the engine efficiency map may not be available.

scholarly journals Research on energy management strategy considering battery life for plug-in hybrid electric vehicle

2018 ◽  
Vol 10 (9) ◽  
pp. 168781401879776 ◽  
Author(s):  
Jianjun Hu ◽  
Zhihua Hu ◽  
Xiyuan Niu ◽  
Qin Bai
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicle ◽  
Energy Management ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Battery Life ◽  
Energy Management Strategy ◽  
Driving Cycles ◽  
Comprehensive Test ◽  
Hybrid Electric

To improve the fuel efficiency and battery life-span of plug-in hybrid electric vehicle, the energy management strategy considering battery life decay is proposed. This strategy is optimized by genetic algorithm, aiming to reduce the fuel consumption and battery life decay of plug-in hybrid electric vehicle. Besides, to acquire better drive-cycle adaptability, driving patterns are recognized with probabilistic neural network. The standard driving cycles are divided into urban congestion cycle, highway cycle, and urban suburban cycle; the optimized energy management strategies in three representative driving cycles are established; meanwhile, a comprehensive test driving cycle is constructed to verify the proposed strategies. The results show that adopting the optimized control strategies, fuel consumption, and battery’s life decay drop by 1.9% and 3.2%, respectively. While using the drive-cycle recognition, the features of different driving cycles can be identified, and based on it, the vehicle can choose appropriate control strategy in different driving conditions. In the comprehensive test driving cycle, after recognizing driving cycles, fuel consumption and battery’s life decay drop by 8.6% and 0.3%, respectively.

Modeling of engine thermal dynamics and its application in energy management of HEVs considering engine warming-up

2021 ◽  
pp. 146808742110445
Author(s):  
Hongqing Chu ◽  
Haoyun Shi ◽  
Yuyao Jiang ◽  
Tielong Shen
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Management Strategy ◽  
Dynamic Programming Algorithm ◽  
Optimal Solution ◽  
Degree Of Approximation ◽  
Programming Algorithm ◽  
Energy Management Strategy ◽  
Thermal Dynamics ◽  
Behavior Simulation

The process of engine warming-up leads to additional fuel consumption. Energy management strategy considering engine warming-up is expected to further improve the energy economy of hybrid electric vehicles. This study provides a simple yet practical model for engine thermal dynamics. Then, the optimization problem of energy management considering engine warming-up is formulated on the basis of the control-oriented engine thermal dynamics. Thereafter, the optimal solution is derived by using the dynamic programming algorithm. Finally, the proposed engine thermal dynamics and energy management strategy are evaluated through simulation and experiments. Results show that the established engine thermal model effectively captures the main thermal behavior, simulation results reveal a high degree of approximation to experimental results for the engine temperature and fuel consumption, and the energy management strategy with engine temperature can further improve the energy efficiency.

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