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    A Multi-objective Optimization Control Strategy of a Range-Extended Electric Vehicle for the Trip Range and Road Gradient Adaption

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    https://www.riss.kr/link?id=A109100811

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    The road gradient and trip range are of great signifi cance in fuel consumption and emissions of a range-extended electric vehicle (REEV). However, the traditional energy management strategy failed to consider the road gradient. To address this issue, a multi-objective optimization adaptive control strategy is proposed to improve the fuel consumption and emissions of the REEVs. Firstly, a multi-objective optimization adaptive control strategy is developed based the equivalent consumption minimization strategy integrated with adaptive equivalent factor (EF). The EF is updating according to the road slope by using a proportional-integral controller. To investigate the impacts of the road gradient on emissions, the numerical models between road gradient and emissions are established. Furthermore, an optimal torque distribution strategy is proposed according to the weights of fuel and emissions, which realizes the tracking of the SOC trajectory and improves the fuel economy and emission performance of the vehicle. Finally, various strategies are carried out to verify the superiority of the proposed strategy by numerical validations. Compared with the control strategy considered fuel consumption only, the validation results show that the engine CO, HC, and NOx are reduced by 9.47, 2.33, and 4.10%, respectively, while compromising fuel economy by 3.3%.
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    The road gradient and trip range are of great signifi cance in fuel consumption and emissions of a range-extended electric vehicle (REEV). However, the traditional energy management strategy failed to consider the road gradient. To address this issue,...

    The road gradient and trip range are of great signifi cance in fuel consumption and emissions of a range-extended electric vehicle (REEV). However, the traditional energy management strategy failed to consider the road gradient. To address this issue, a multi-objective optimization adaptive control strategy is proposed to improve the fuel consumption and emissions of the REEVs. Firstly, a multi-objective optimization adaptive control strategy is developed based the equivalent consumption minimization strategy integrated with adaptive equivalent factor (EF). The EF is updating according to the road slope by using a proportional-integral controller. To investigate the impacts of the road gradient on emissions, the numerical models between road gradient and emissions are established. Furthermore, an optimal torque distribution strategy is proposed according to the weights of fuel and emissions, which realizes the tracking of the SOC trajectory and improves the fuel economy and emission performance of the vehicle. Finally, various strategies are carried out to verify the superiority of the proposed strategy by numerical validations. Compared with the control strategy considered fuel consumption only, the validation results show that the engine CO, HC, and NOx are reduced by 9.47, 2.33, and 4.10%, respectively, while compromising fuel economy by 3.3%.

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    참고문헌 (Reference)

    1 Peng, J., "Rule based energy management strategy for a series–parallel plug-in hybrid electric bus optimized by dynamic programming" 185 : 1633-1643, 2017

    2 He, H., "Road grade prediction for predictive energy management in hybrid electric vehicles" 105 : 2438-2444, 2017

    3 Wang, Y., "Research on energy optimization control strategy of the hybrid electric vehicle based on Pontryagin’s minimum principle" 72 : 203-213, 2018

    4 Lin, X., "Predictive-ECMS based degradation protective control strategy for a fuel cell hybrid electric vehicle considering uphill condition" 12 : 100168-, 2022

    5 Zhang, S., "Pontryagin’s minimum principle-based power management of a dual-motor-driven electric bus" 159 : 370-380, 2015

    6 Wegmann, R., "Optimized operation of hybrid battery systems for electric vehicles using deterministic and stochastic dynamic programming" 14 : 22-38, 2017

    7 Schori, M., "Optimal calibration of map-based energy management for plug-In parallel hybrid confi gurations : A hybrid optimal control approach" 64 (64): 3897-3907, 2015

    8 Lin, X., "Online recursive power management strategy based on the reinforcement learning algorithm with cosine similarity and a forgetting factor" 68 (68): 5013-5023, 2020

    9 Silva, S. F., "Multi-objective optimization design and control of plugin hybrid electric vehicle powertrain for minimization of energy consumption, exhaust emissions and battery degradation" 234 : 113909-, 2021

    10 Xie, S., "Model predictive energy management for plug-in hybrid electric vehicles considering optimal battery depth of discharge" 173 : 667-678, 2019

    1 Peng, J., "Rule based energy management strategy for a series–parallel plug-in hybrid electric bus optimized by dynamic programming" 185 : 1633-1643, 2017

    2 He, H., "Road grade prediction for predictive energy management in hybrid electric vehicles" 105 : 2438-2444, 2017

    3 Wang, Y., "Research on energy optimization control strategy of the hybrid electric vehicle based on Pontryagin’s minimum principle" 72 : 203-213, 2018

    4 Lin, X., "Predictive-ECMS based degradation protective control strategy for a fuel cell hybrid electric vehicle considering uphill condition" 12 : 100168-, 2022

    5 Zhang, S., "Pontryagin’s minimum principle-based power management of a dual-motor-driven electric bus" 159 : 370-380, 2015

    6 Wegmann, R., "Optimized operation of hybrid battery systems for electric vehicles using deterministic and stochastic dynamic programming" 14 : 22-38, 2017

    7 Schori, M., "Optimal calibration of map-based energy management for plug-In parallel hybrid confi gurations : A hybrid optimal control approach" 64 (64): 3897-3907, 2015

    8 Lin, X., "Online recursive power management strategy based on the reinforcement learning algorithm with cosine similarity and a forgetting factor" 68 (68): 5013-5023, 2020

    9 Silva, S. F., "Multi-objective optimization design and control of plugin hybrid electric vehicle powertrain for minimization of energy consumption, exhaust emissions and battery degradation" 234 : 113909-, 2021

    10 Xie, S., "Model predictive energy management for plug-in hybrid electric vehicles considering optimal battery depth of discharge" 173 : 667-678, 2019

    11 Huang, Y., "Model predictive control power management strategies for HEVs : A review" 341 : 91-106, 2017

    12 Hu, X., "Model predictive control of hybrid electric vehicles for fuel economy, emission reductions, and inter-vehicle safety in car-following scenarios" 196 : 117101-, 2020

    13 Zhang, H., "Learning-based supervisory control of dual mode engine-based hybrid electric vehicle with reliance on multivariate trip information" 257 : 115450-, 2022

    14 Lin, X., "Intelligent energy management strategy based on an improved reinforcement learning algorithm with exploration factor for a plug-in PHEV" 23 (23): 8725-8735, 2021

    15 Liang, J., "Fuzzy energy management optimization for a parallel hybrid electric vehicle using chaotic non-dominated sorting genetic algorithm" 56 (56): 149-163, 2015

    16 Elbert, P., "Engine on/off control for the energy management of a serial hybrid electric bus via convex optimization" 63 (63): 3549-3559, 2014

    17 Biswas, A., "Energy management systems for electrifi ed powertrains : State-of-the-art review and future trends" 68 (68): 6453-6467, 2019

    18 Xi, L. H., "Energy management strategy optimization of extended-range electric vehicle based on dynamic programming" 18 (18): 148-156, 2018

    19 Zhang, F., "Energy management strategies of connected HEVs and PHEVs : Recent progress and outlook" 73 : 235-256, 2019

    20 Martínez, C., "Energy management in plug-in hybrid electric vehicles : Recent progress and a connected vehicles perspective" 66 (66): 4534-4549, 2017

    21 Hu, X., "Cost-optimal energy management of hybrid electric vehicles using fuel cell/battery health-Aware predictive control" 35 (35): 382-392, 2019

    22 Jiang, Q., "Comparative study of real-time HEV energy management strategies" 66 (66): 10875-10888, 2017

    23 Lin, X., "Charge depleting range dynamic strategy with power feedback considering fuel-cell degradation" 80 : 345-365, 2020

    24 Lin, X., "Battery aging-aware energy management strategy with dual-state feedback for improving life cycle economy by using multi-neural networks learning algorithm" 46 : 103890-, 2022

    25 Wahono, B., "Analysis of range extender electric vehicle performance using vehicle simulator" 68 : 409-418, 2015

    26 Zhang, S., "Adaptively coordinated optimization of battery aging and energy management in plug-in hybrid electric buses" 256 : 113891-, 2019

    27 Yang, C., "Adaptive real-time optimal energy management strategy based on equivalent factors optimization for plug-in hybrid electric vehicle" 203 : 883-896, 2017

    28 Lin, X., "A trip distance adaptive real-time optimal energy management strategy for a plug-in hybrid vehicle integrated driving condition prediction" 52 : 105055-, 2022

    29 Zeng, X., "A parallel hybrid electric vehicle energy management strategy Using stochastic model predictive control with road grade preview" 23 (23): 2416-2423, 2015

    30 Sezer, V., "A novel ECMS and combined cost map approach for high-effi ciency series hybrid electric vehicles" 60 (60): 3557-3570, 2011

    31 Wang, W., "A multi-objective optimization energy management strategy for power split HEV based on velocity prediction" 238 : 121714-, 2022

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