Hybrid Electric Vehicle Energy Management and Control Based on Battery Energy Balance

2013 ◽  
Vol 273 ◽  
pp. 764-767
Author(s):  
Bin Yan ◽  
Yan Qing Hu ◽  
Ting Yan ◽  
Pei Pei Ma ◽  
Lin Yang
Keyword(s):  
Energy Balance ◽  
Electric Vehicle ◽  
Energy Management ◽  
Fuel Economy ◽  
Power Efficiency ◽  
Hybrid Electric Vehicle ◽  
Real Time Control ◽  
Energy Management Strategy ◽  
Hybrid Electric ◽  
Battery Energy

Hybrid electric vehicle has better power and economy than conventional vehicle attributed to power efficiency range is optimized by battery energy. So making battery energy balance not only can ensure hybrid power system operate normally, but also is the key role in meeting vehicle drivability and improving fuel economy effectively. This paper analyze of the regenerating and using of battery energy. Real-time control and global optimization is used to adjust energy management strategy, the adaptive control strategy also introduced to making energy power balance on the basis of maximum fuel economy in the driving cycle.

scholarly journals Modeling and energy management strategy research of a power-split hybrid electric vehicle

2020 ◽  
Vol 12 (10) ◽  
pp. 168781402096262
Author(s):  
Yupeng Zou ◽  
Ruchen Huang ◽  
Xiangshu Wu ◽  
Baolong Zhang ◽  
Qiang Zhang ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Energy Management ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Research Work ◽  
Energy Management Strategy ◽  
Power Sources ◽  
Power Split ◽  
Hybrid Electric ◽  
The Impact

A power-split hybrid electric vehicle with a dual-planetary gearset is researched in this paper. Based on the lever analogy method of planetary gearsets, the power-split device is theoretically modeled, and the driveline simulation model is built by using vehicle modeling and simulation toolboxes in MATLAB. Six operation modes of the vehicle are discussed in detail, and the kinematic constraint behavior of power sources are analyzed. To verify the rationality of the modeling, a rule-based control strategy (RB) and an adaptive equivalent consumption minimization strategy (A-ECMS) are designed based on the finite state machine and MATLAB language respectively. In order to demonstrate the superiority of A-ECMS in fuel-saving and to explore the impact of different energy management strategies on emission, fuel economy and emission performance of the vehicle are simulated and analyzed under UDDS driving cycle. The simulation results of the two strategies are compared in the end, shows that the modeling is rational, and compared with RB strategy, A-ECMS ensures charge sustaining better, enables power sources to work in more efficient areas, and improves fuel economy by 8.65%, but significantly increases NOx emissions, which will be the focus of the next research work.

Multi-objective real-time optimization energy management strategy for plug-in hybrid electric vehicle

2018 ◽  
Vol 233 (5) ◽  
pp. 1067-1080 ◽  
Author(s):  
Siyu Du ◽  
Yiyong Yang ◽  
Congzhi Liu ◽  
Fahad Muhammad
Keyword(s):  
Electric Vehicle ◽  
Energy Management ◽  
Fuel Economy ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Energy Management Strategy ◽  
Improve Fuel Economy ◽  
Hybrid Electric ◽  
Multiple Operation ◽  
Real Time Optimization

Plug-in hybrid electric vehicle provides remarkable results for emission reduction and fuel improvement in the current driving cycles. With the appropriate energy management strategy, the torque can be split by switching of multiple operation modes to improve fuel economy. However, in the process, not only the noticeable jerk or torque fluctuation, which may result in vibration of the drivetrain and unpleasant driving sensation, but also the frequent motor-start-engine process would be triggered, which is accompanied by extra fuel consumption and abrasion of the clutch. Therefore, high attention should be paid to reduce the excess operating times of the motor-start-engine process and take advantage of multiple operation modes to improve fuel economy in plug-in hybrid electric vehicle. To solve this problem, a multi-objective real-time optimization energy management strategy is proposed. First, the motor-start-engine dynamic model of 2-degree-of-freedom is established. Then, the motor-start-engine process is analyzed based on a large number of real-world data, and the cost of the motor-start-engine process is quantified for optimization. What’s more, the optimal torque distribution is realized through the powertrain system. Finally, the proposed strategy is verified by the simulation and experiment platform. Results show that the proposed strategy can greatly improve fuel economy, thereby reducing the excess operating times of the motor-start-engine process.

Fuzzy Torque Distribution Control for a Parallel Hybrid Electric Vehicle

2001 ◽  
Author(s):  
Jong-Seob Won ◽  
Reza Langari
Keyword(s):  
Electric Vehicle ◽  
Energy Management ◽  
Hybrid Electric Vehicle ◽  
Energy Management Strategy ◽  
Torque Distribution ◽  
Parallel Hybrid Electric Vehicle ◽  
Cycle Simulation ◽  
Mode Of Operation ◽  
Parallel Hybrid ◽  
Hybrid Electric

Abstract A fuzzy torque distribution controller for energy management (and emission control) of a parallel-hybrid electric vehicle is proposed. The proposed controller is implemented in terms of a hierarchical architecture which incorporates the mode of operation of the vehicle as well as empirical knowledge of energy flow in each mode. Moreover, the rule set for each mode of operation of the vehicle is designed in view of an overall energy management strategy that ranges from maximal emphasis on battery charge sustenance to complete reliance on the electrical power source. The proposed control system is evaluated via computational simulations under the FTP75 urban drive cycle. Simulation results reveal that the proposed fuzzy torque distribution strategy is effective over the entire operating range of the vehicle in terms of performance, fuel economy as well as emissions.

scholarly journals Multi-objective Parameters Optimization for HEV Based on improved Particle Swarm Algorithm

2019 ◽  
Vol 118 ◽  
pp. 02005
Author(s):  
Ying Ai ◽  
Yuanjie Gao ◽  
dongsheng Liu
Keyword(s):  
Electric Vehicle ◽  
Energy Management ◽  
Fuel Economy ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Fuzzy Controller ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Energy Management Strategy ◽  
Multi Objective

Hybrid electric vehicle fuel consumption and emissions are closely related to its energy management strategy. A fuzzy controller of energy management using vehicle torque request and battery state of charge (SOC) as inputs, engine torque as output is designed in this paper foe parallel hybrid electric vehicle. And a multi-objective mathematical function which purpose on maximize fuel economy and minimize emissions is also established, in order to improve the adaptive ability and the control precision of basic fuzzy controller, this paper proposed an improved particle swarm algorithm that based on dynamic learning factor and adaptive inertia weight to optimize the control parameters. Simulation results based on ADVISOR software platform show that the optimized energy management strategy has a better distribution of engine and motor torque, which helps to improved the vehicle’s fuel economy and exhaust emission performance.

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