Application of Parallel Chaos Optimization Algorithm for Plug-in Hybrid Electric Vehicle Design

2014 ◽  
Vol 24 (01) ◽  
pp. 1450001 ◽  
Author(s):  
Xiaolan Wu ◽  
Guifang Guo ◽  
Jun Xu ◽  
Binggang Cao
Keyword(s):  
Optimization Algorithm ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Optimization Problem ◽  
Optimization Method ◽  
Vehicle Performance ◽  
Chaos Optimization ◽  
Performance Requirements ◽  
Chaos Optimization Algorithm ◽  
Hybrid Electric

Plug-in hybrid electric vehicles (PHEVs) have been offered as alternatives that could greatly reduce fuel consumption relative to conventional vehicles. A successful PHEV design requires not only optimal component sizes but also proper control strategy. In this paper, a global optimization method, called parallel chaos optimization algorithm (PCOA), is used to optimize simultaneously the PHEV component sizes and control strategy. In order to minimize the cost, energy consumption (EC), and emissions, a multiobjective nonlinear optimization problem is formulated and recast as a single objective optimization problem by weighted aggregation. The driving performance requirements of the PHEV are considered as the constraints. In addition, to evaluate the objective function, the optimization process is performed over three typical driving cycles including Urban Dynamometer Driving Schedule (UDDS), Highway Fuel Economy Test (HWFET), and New European Driving Cycle (NEDC). The simulation results show the effectiveness of the proposed approach for reducing the fuel cost, EC and emissions while ensuring that the vehicle performance has not been sacrificed.

scholarly journals Multiobjective optimisation of a series hybrid electric vehicle using DIRECT algorithm

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Abdelmoula Rihab ◽  
◽  
Ben Hadj Naourez ◽  
Chaieb Mohamed ◽  
Neji Rafik ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Vehicle Performance ◽  
Performance Requirements ◽  
Toxic Emissions ◽  
Series Hybrid Electric Vehicle ◽  
Hybrid Electric ◽  
Fuel Consumption And Emissions

With the economic development, transportation in the city becomes more crowded. Furthermore, fuel consumption is causing a serious problem of pollution in the urban environment. Hybrid electric vehicles are considered as a good solution compared to conventional internal combustion engine vehicles. In order to solve those problems, the components parameters of a series hybrid electric vehicle are selected and tested with the ADvanced VehIcle SimulatOR (ADVISOR) simulation tool, which is a software-based on Matlab_simulink. Then, an optimisation was done to minimise simultaneous fuel consumption and emissions (HC, CO, and NOx) of the vehicle engine. In addition, the driving performance requirements are also examined during the urban dynamometer driving schedule (UDDS) to fix their optimal control parameters. Finally, the results show that those steps help reduce fuel consumption and emissions while guaranteeing vehicle performance. Hence, the series hybrid electric vehicle greatly improves fuel economy and reduces toxic emissions.

Research on regenerative braking control strategy of plug-in hybrid electric vehicle considering CVT ratio rate of change

2017 ◽  
Vol 232 (14) ◽  
pp. 1931-1943 ◽  
Author(s):  
Jianjun Hu ◽  
Zihan Guo ◽  
Hang Peng ◽  
Dawei Zheng
Keyword(s):  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Control Strategies ◽  
Dynamic Change ◽  
Optimization Method ◽  
Rate Of Change ◽  
Regenerative Braking ◽  
Hybrid Electric ◽  
Braking Control ◽  
Braking Process

At present, the regenerative braking control strategies for hybrid electric vehicles equipped with continuously variable transmission (CVT) mainly focus on improving the regenerative braking efficiency. But the influence of dynamic change of the CVT ratio is not considered with regard to the intended braking effect. For a CVT ratio control strategy based on steady-state optimal efficiency, the performance of motor-only braking and engine/motor combined braking modes are analyzed. The analysis of these modes shows that actual braking strength deviates from that required during the dynamic braking process. After analyzing the dynamic characteristics of a transmission system, a CVT ratio control strategy based on the limitations of the ratio rate of change is proposed, with the use of a discrete exhaustive optimization method. The simulation results show that, under a variety of braking conditions, the proposed regenerative braking control strategy can make the actual braking strength follow the requirements and recover more braking energy.

Solving Robust Reliability Index Based on the Mutative Scale Chaos Optimization Algorithm

2013 ◽  
Vol 838-841 ◽  
pp. 579-585
Author(s):  
Feng Zhang ◽  
Xin Dang He ◽  
Hua Nan ◽  
Hao Ren
Keyword(s):  
Computational Complexity ◽  
Optimization Algorithm ◽  
Reliability Index ◽  
Optimization Method ◽  
Reliability Model ◽  
Chaos Optimization ◽  
Chaos Optimization Algorithm ◽  
Optimization Variable ◽  
Novel Method ◽  
Robust Reliability

A novel method based on the mutative scale chaos optimization algorithm is proposed to solve the robust reliability index of non-probabilistic reliability model. Compared with the basic chaos optimization method, this novel method can minimize searching area of optimization variable and change the adjustable parameters of next search stage for improving the optimization performance. The proposed optimization algorithm is more efficient and has smaller computational complexity in solving robust reliability index. The feasibility and efficiency of the proposed method are demonstrated by two examples.

scholarly journals A Component-Sizing Methodology for a Hybrid Electric Vehicle Using an Optimization Algorithm

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3147
Author(s):  
Kiyoung Kim ◽  
Namdoo Kim ◽  
Jongryeol Jeong ◽  
Sunghwan Min ◽  
Horim Yang ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Electric Vehicle ◽  
Optimization Algorithm ◽  
Hybrid Electric Vehicle ◽  
New Technologies ◽  
New Technology ◽  
Dynamic Performance ◽  
Minimum Principle ◽  
Component Sizing ◽  
Hybrid Electric

Many leading companies in the automotive industry have been putting tremendous effort into developing new powertrains and technologies to make their products more energy efficient. Evaluating the fuel economy benefit of a new technology in specific powertrain systems is straightforward; and, in an early concept phase, obtaining a projection of energy efficiency benefits from new technologies is extremely useful. However, when carmakers consider new technology or powertrain configurations, they must deal with a trade-off problem involving factors such as energy efficiency and performance, because of the complexities of sizing a vehicle’s powertrain components, which directly affect its energy efficiency and dynamic performance. As powertrains of modern vehicles become more complicated, even more effort is required to design the size of each component. This study presents a component-sizing process based on the forward-looking vehicle simulator “Autonomie” and the optimization algorithm “POUNDERS”; the supervisory control strategy based on Pontryagin’s Minimum Principle (PMP) assures sufficient computational system efficiency. We tested the process by applying it to a single power-split hybrid electric vehicle to determine optimal values of gear ratios and each component size, where we defined the optimization problem as minimizing energy consumption when the vehicle’s dynamic performance is given as a performance constraint. The suggested sizing process will be helpful in determining optimal component sizes for vehicle powertrain to maximize fuel efficiency while dynamic performance is satisfied. Indeed, this process does not require the engineer’s intuition or rules based on heuristics required in the rule-based process.

Hierarchical energy management strategy considering switching schedule for a dual-mode hybrid electric vehicle

2021 ◽  
pp. 095440702110297
Author(s):  
Hui Liu ◽  
Rui Liu ◽  
Riming Xu ◽  
Lijin Han ◽  
Shumin Ruan
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Control Strategy ◽  
Power Distribution ◽  
Hybrid Electric Vehicle ◽  
Hierarchical Control ◽  
Management Problem ◽  
Energy Management Strategy ◽  
Dual Mode ◽  
Hybrid Electric

Energy management strategies are critical for hybrid electric vehicles (HEVs) to improve fuel economy. To solve the dual-mode HEV energy management problem combined with switching schedule and power distribution, a hierarchical control strategy is proposed in this paper. The mode planning controller is twofold. First, the mode schedule is obtained according to the mode switch map and driving condition, then a switch hunting suppression algorithm is proposed to flatten the mode schedule through eliminating unnecessary switch. The proposed algorithm can reduce switch frequency while fuel consumption remains nearly unchanged. The power distribution controller receives the mode schedule and optimizes power distribution between the engine and battery based on the Radau pseudospectral knotting method (RPKM). Simulations are implemented to verify the effectiveness of the proposed hierarchical control strategy. For the mode planning controller, as the flattening threshold value increases, the fuel consumption remains nearly unchanged, however, the switch frequency decreases significantly. For the power distribution controller, the fuel consumption obtained by RPKM is 4.29% higher than that of DP, while the elapsed time is reduced by 92.53%.

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