Green Energy and Intelligent Transportation最新文献_第10页

Trajectory-tracking controller for vehicles on inclined road based on Udwadia – Kalaba equation 基于Udwadia - Kalaba方程的倾斜道路车辆轨迹跟踪控制器

Green Energy and Intelligent Transportation Pub Date : 2022-12-01 DOI: 10.1016/j.geits.2022.100021

Xingyu Li , Xinle Gong , Jin Huang , Ye-Hwa Chen

{"title":"Trajectory-tracking controller for vehicles on inclined road based on Udwadia – Kalaba equation","authors":"Xingyu Li , Xinle Gong , Jin Huang , Ye-Hwa Chen","doi":"10.1016/j.geits.2022.100021","DOIUrl":"10.1016/j.geits.2022.100021","url":null,"abstract":"<div><p>Vehicle lateral control is an important subtask of vehicle autonomous driving. There are many external disturbances that will affect the lateral control accuracy of the vehicle, and the inclination of the road is one of the most important ones. The inclined road will lead to additional lateral forces on the vehicle and will also change the magnitude of support force on the vehicle. The change of lateral force and support force will ultimately affect the trajectory tracking performance of the vehicle. Most of the current trajectory tracking methods only consider the trajectory tracking problem on the plane. If the influence of the road surface is considered in the design of the vehicle's trajectory tracking controller, the dynamic response and the tracking accuracy of the vehicle can be improved. This paper proposes a method based on Udwadia–Kalaba equation to calculate the normal and lateral force on a vehicle tracking a desired trajectory on an inclined road. Further, a trajectory tracking controller that considers the road inclination is designed. Finally, the simulation of trajectory tracking performance with an inclination angle is carried out to verify the effectiveness of the proposed controller.</p></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773153722000214/pdfft?md5=7fa5633003f7d4b84ff724171f7e8a5d&pid=1-s2.0-S2773153722000214-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75505737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A review on cooperative perception and control supported infrastructure-vehicle system 基于协同感知与控制的基础设施-车辆系统研究进展

Green Energy and Intelligent Transportation Pub Date : 2022-12-01 DOI: 10.1016/j.geits.2022.100023

Guizhen Yu, Han Li, Yunpeng Wang, Peng Chen, Bin Zhou

{"title":"A review on cooperative perception and control supported infrastructure-vehicle system","authors":"Guizhen Yu, Han Li, Yunpeng Wang, Peng Chen, Bin Zhou","doi":"10.1016/j.geits.2022.100023","DOIUrl":"10.1016/j.geits.2022.100023","url":null,"abstract":"<div><p>With the rapid development of connected autonomous vehicles (CAVs), both road infrastructure and transport are experiencing a profound transformation. In recent years, the cooperative perception and control supported infrastructure-vehicle system (IVS) attracted increasing attention in the field of intelligent transportation systems (ITS). The perception information of surrounding objects can be obtained by various types of sensors or communication networks. Control commands generated by CAVs or infrastructure can be executed promptly and accurately to improve the overall performance of the transportation system in terms of safety, efficiency, comfort and energy saving. This study presents a comprehensive review of the research progress achieved upon cooperative perception and control supported IVS over the past decade. By focusing on the essential interactions between infrastructure and CAVs and between CAVs, the infrastructure-vehicle cooperative perception and control methods are summarized and analyzed. Furthermore, the mining site as a closed scenario was used to show the current application of IVS. Finally, the existing issues of the cooperative perception and control technology implementation are discussed, and the recommendation for future research directions are proposed.</p></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773153722000238/pdfft?md5=804e6ad0e15997aa273f6767a1b09d6d&pid=1-s2.0-S2773153722000238-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89231726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

A methodology for assessing the urban supply of on-street delivery bays 一套评估市区街道收货位供应的方法

Green Energy and Intelligent Transportation Pub Date : 2022-12-01 DOI: 10.1016/j.geits.2022.100024

Antonio Comi , José Luis Moura , Sara Ezquerro

{"title":"A methodology for assessing the urban supply of on-street delivery bays","authors":"Antonio Comi , José Luis Moura , Sara Ezquerro","doi":"10.1016/j.geits.2022.100024","DOIUrl":"10.1016/j.geits.2022.100024","url":null,"abstract":"<div><p>The loading and unloading operations carried out by transport and logistics operators have a strong impact on city mobility if they are not performed correctly. If loading/unloading bays, i.e., delivery bays (DB), are not available for freight vehicle operations, operators may opt to double park or park on the sidewalk where there is no strong enforcement of these laws, with significant impact on congestion. This paper proposes a methodology for verifying and designing the number of delivery bays needed for freight vehicles for not interfere with cars or pedestrians. The methodology consists of two stages: in the first stage, an initial estimation is made using queueing theory. Subsequently, in the second stage, using such tentative scenario, in order to take into account the system stochasticity involving different entities, a discrete event simulation is performed to more realistically verify and upgrade (if necessary) the number of delivery bays to obtain the expected outcomes. The methodology was applied in the inner area of Santander (Spain). The study area was subdivided into 29 zones where the methodology was applied individually. The results indicated that none of these zones currently have an optimal number of delivery bays to satisfy demand. In some zones, there is an excess of delivery bays, although in most of them, there is a deficit which can cause significant impacts on traffic. The method proposed can be an effective tool to be used by city planners for improving freight operations in urban areas limiting the negative impacts produced in terms of internal and external costs.</p></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S277315372200024X/pdfft?md5=664b750c2bbe4108514984402922efd4&pid=1-s2.0-S277315372200024X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79590371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A hybrid motion planning framework for autonomous driving in mixed traffic flow 混合交通流下自动驾驶的混合运动规划框架

Green Energy and Intelligent Transportation Pub Date : 2022-12-01 DOI: 10.1016/j.geits.2022.100022

Lei Yang , Chao Lu , Guangming Xiong , Yang Xing , Jianwei Gong

{"title":"A hybrid motion planning framework for autonomous driving in mixed traffic flow","authors":"Lei Yang , Chao Lu , Guangming Xiong , Yang Xing , Jianwei Gong","doi":"10.1016/j.geits.2022.100022","DOIUrl":"10.1016/j.geits.2022.100022","url":null,"abstract":"<div><p>As a core part of an autonomous driving system, motion planning plays an important role in safe driving. However, traditional model- and rule-based methods lack the ability to learn interactively with the environment, and learning-based methods still have problems in terms of reliability. To overcome these problems, a hybrid motion planning framework (HMPF) is proposed to improve the performance of motion planning, which is composed of learning-based behavior planning and optimization-based trajectory planning. The behavior planning module adopts a deep reinforcement learning (DRL) algorithm, which can learn from the interaction between the ego vehicle (EV) and other human-driven vehicles (HDVs), and generate behavior decision commands based on environmental perception information. In particular, the intelligent driver model (IDM) calibrated based on real driving data is used to drive HDVs to imitate human driving behavior and interactive response, so as to simulate the bidirectional interaction between EV and HDVs. Meanwhile, trajectory planning module adopts the optimization method based on road Frenet coordinates, which can generate safe and comfortable desired trajectory while reducing the solution dimension of the problem. In addition, trajectory planning also exists as a safety hard constraint of behavior planning to ensure the feasibility of decision instruction. The experimental results demonstrate the effectiveness and feasibility of the proposed HMPF for autonomous driving motion planning in urban mixed traffic flow scenarios.</p></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773153722000226/pdfft?md5=0012d1b315e0461d4f8ec9dd7333de19&pid=1-s2.0-S2773153722000226-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82767307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Online power management strategy for plug-in hybrid electric vehicles based on deep reinforcement learning and driving cycle reconstruction 基于深度强化学习和行驶循环重构的插电式混合动力汽车在线电源管理策略

Green Energy and Intelligent Transportation Pub Date : 2022-09-01 DOI: 10.1016/j.geits.2022.100016

Zhiyuan Fang , Zeyu Chen , Quanqing Yu , Bo Zhang , Ruixin Yang

{"title":"Online power management strategy for plug-in hybrid electric vehicles based on deep reinforcement learning and driving cycle reconstruction","authors":"Zhiyuan Fang , Zeyu Chen , Quanqing Yu , Bo Zhang , Ruixin Yang","doi":"10.1016/j.geits.2022.100016","DOIUrl":"10.1016/j.geits.2022.100016","url":null,"abstract":"<div><p>This paper proposes a novel power management strategy for plug-in hybrid electric vehicles based on deep reinforcement learning algorithm. Three parallel soft actor-critic (SAC) networks are trained for high speed, medium speed, and low-speed conditions respectively; the reward function is designed as minimizing the cost of energy cost and battery aging. During operation, the driving condition is recognized at each moment for the algorithm invoking based on the learning vector quantization (LVQ) neural network. On top of that, a driving cycle reconstruction algorithm is proposed. The historical speed segments that were recorded during the operation are reconstructed into the three categories of high speed, medium speed, and low speed, based on which the algorithms are online updated. The SAC-based control strategy is evaluated based on the standard driving cycles and Shenyang practical data. The results indicate the presented method can obtain the effect close to dynamic programming and can be further improved by up to 6.38% after the online update for uncertain driving conditions.</p></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773153722000160/pdfft?md5=9e2e034b0ae6e2c1c67069904bb1de13&pid=1-s2.0-S2773153722000160-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75277342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Driver-automation shared steering control considering driver neuromuscular delay characteristics based on stackelberg game 基于stackelberg博弈的考虑驾驶员神经肌肉延迟特性的驾驶自动化共享转向控制

Green Energy and Intelligent Transportation Pub Date : 2022-09-01 DOI: 10.1016/j.geits.2022.100027

Jun Liu , Hongyan Guo , Wanqing Shi , Qikun Dai , Jiaming Zhang

{"title":"Driver-automation shared steering control considering driver neuromuscular delay characteristics based on stackelberg game","authors":"Jun Liu , Hongyan Guo , Wanqing Shi , Qikun Dai , Jiaming Zhang","doi":"10.1016/j.geits.2022.100027","DOIUrl":"10.1016/j.geits.2022.100027","url":null,"abstract":"<div><p>To promote the intelligent vehicle safety and reduce the driver steering workload, stackelberg game theory is adopted to design the shared steering control strategy that takes the driver neuromuscular delay characteristics into account. First, a shared steering control framework with adjustable driving weight is proposed, and a coupling interaction model considering the driver neuromuscular delay characteristics is constructed by using the stackelberg game theory. Moreover, the driver-automation optimal control strategy is deduced theoretically when the game equilibrium is reached. Finally, simulation and virtual driving tests are carried out to verify the superiority of the proposed method. The results illustrate that the raised method can enhance the vehicle safety with low driving weight intervention, and it can achieve better auxiliary effect with less control cost. In addition, the driver-in-the-loop test results show that the proposed strategy can achieve better performance in assisting drivers with low driving skills.</p></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773153722000275/pdfft?md5=72d6309b410066d9b43ff6e48f71b5f7&pid=1-s2.0-S2773153722000275-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74483625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A transferable energy management strategy for hybrid electric vehicles via dueling deep deterministic policy gradient 基于深度确定性政策梯度的混合动力汽车可转移能量管理策略

Green Energy and Intelligent Transportation Pub Date : 2022-09-01 DOI: 10.1016/j.geits.2022.100018

Jingyi Xu , Zirui Li , Guodong Du , Qi Liu , Li Gao , Yanan Zhao

{"title":"A transferable energy management strategy for hybrid electric vehicles via dueling deep deterministic policy gradient","authors":"Jingyi Xu , Zirui Li , Guodong Du , Qi Liu , Li Gao , Yanan Zhao","doi":"10.1016/j.geits.2022.100018","DOIUrl":"10.1016/j.geits.2022.100018","url":null,"abstract":"<div><p>Due to the high mileage and heavy load capabilities of hybrid electric vehicles (HEVs), energy management becomes crucial in improving energy efficiency. To avoid the over-dependence on the hard-crafted models, deep reinforcement learning (DRL) is utilized to learn more precise energy management strategies (EMSs), but cannot generalize well to different driving situations in most cases. When driving cycles are changed, the neural network needs to be retrained, which is a time-consuming and laborious task. A more efficient transferable way is to combine DRL algorithms with transfer learning, which can utilize the knowledge of the driving cycles in other new driving situations, leading to better initial performance and a faster training process to convergence. In this paper, we propose a novel transferable EMS by incorporating the DRL method and dueling network architecture for HEVs. Simulation results indicate that the proposed method can generalize well to new driving cycles, with comparably initial performance and faster convergence in the training process.</p></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773153722000184/pdfft?md5=dd2f51aadf812b0b489268506b3abfec&pid=1-s2.0-S2773153722000184-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87959648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

A branch current estimation and correction method for a parallel connected battery system based on dual BP neural networks 基于双BP神经网络的并联电池系统支路电流估计与校正方法

Green Energy and Intelligent Transportation Pub Date : 2022-09-01 DOI: 10.1016/j.geits.2022.100029

Quanqing Yu , Yukun Liu , Shengwen Long , Xin Jin , Junfu Li , Weixiang Shen

{"title":"A branch current estimation and correction method for a parallel connected battery system based on dual BP neural networks","authors":"Quanqing Yu , Yukun Liu , Shengwen Long , Xin Jin , Junfu Li , Weixiang Shen","doi":"10.1016/j.geits.2022.100029","DOIUrl":"10.1016/j.geits.2022.100029","url":null,"abstract":"<div><p>In the actual use of a parallel battery pack in electric vehicles (EVs), current distribution in each branch will be different due to inconsistence characteristics of each battery cell. If the branch current is approximately calculated by the total current of the battery pack divided by the number of the parallel branches, there will be a large error between the calculated branch current and the real branch current. Adding current sensors to measure each branch current is not practical because of the high cost. Accurate estimation of branch currents can give a safety warning in time when the parallel batteries of EVs are seriously inconsistent. This paper puts forward a method to estimate and correct branch currents based on dual back propagation (BP) neural networks. In the proposed method, one BP neural network is used to estimate branch currents, the other BP neural network is used to reduce the estimation error cause by current pulse excitations. Furthermore, this paper makes discussions on the selection of the best inputs for the dual BP neural networks and the adaptability of the method for different battery capacity and resistence differences. The effectiveness of the proposed method is verified by multiple dynamic conditions of two cells connected in parallel.</p></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773153722000299/pdfft?md5=e98ad54ee91359d943a5d990672c92a0&pid=1-s2.0-S2773153722000299-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79211973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 21

Review of bidirectional DC–DC converter topologies for hybrid energy storage system of new energy vehicles 新能源汽车混合储能系统双向DC-DC变换器拓扑研究进展

Green Energy and Intelligent Transportation Pub Date : 2022-09-01 DOI: 10.1016/j.geits.2022.100010

Jiulong Wang , Bingquan Wang , Lei Zhang , Jianjun Wang , N.I. Shchurov , B.V. Malozyomov

{"title":"Review of bidirectional DC–DC converter topologies for hybrid energy storage system of new energy vehicles","authors":"Jiulong Wang , Bingquan Wang , Lei Zhang , Jianjun Wang , N.I. Shchurov , B.V. Malozyomov","doi":"10.1016/j.geits.2022.100010","DOIUrl":"https://doi.org/10.1016/j.geits.2022.100010","url":null,"abstract":"<div><p>New energy vehicles play a positive role in reducing carbon emissions. To improve the dynamic performance and durability of vehicle powertrain, the hybrid energy storage system of “fuel cell/power battery plus super capacitor” is more used in new energy vehicles. Bidirectional DC–DC converters with wide voltage conversion range are essential for voltage matching and power decoupling between super capacitor and vehicle bus, helping to improve the low input voltage characteristics of super capacitors and realize the recovery of feedback energy. In recent years, the topologies of bidirectional converters have been widely investigated and optimized. Aiming to obtain bidirectional DC–DC converters with wide voltage conversion range suitable for hybrid energy storage system, a review of the research status of non-isolated converters based on impedance networks and isolated converters based on transformer are presented. Additionally, an evaluation system for bidirectional DC–DC topologies for hybrid energy storage system is constructed, providing a reference for designing bidirectional DC–DC converters. The performance of eight typical non-isolated converters and seven typical isolated converters are comprehensively evaluated by using this evaluation system. On this basis, issues about DC–DC converters for hybrid energy storage system are discussed, and some suggestions for the future research directions of DC–DC converters are proposed. The optimization of bidirectional DC–DC converters for hybrid energy storage system from the perspectives of wide bandgap device application, electromagnetic compatibility technology and converter fault diagnosis strategies is the main research direction.</p></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S277315372200010X/pdfft?md5=fc124113c3aa564eb711c418cec10a64&pid=1-s2.0-S277315372200010X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"137156901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep reinforcement learning based energy management strategy for fuel cell/battery/supercapacitor powered electric vehicle 基于深度强化学习的燃料电池/电池/超级电容器动力电动汽车能量管理策略

Green Energy and Intelligent Transportation Pub Date : 2022-09-01 DOI: 10.1016/j.geits.2022.100028

Jie Wang, Jianhao Zhou, Wanzhong Zhao

{"title":"Deep reinforcement learning based energy management strategy for fuel cell/battery/supercapacitor powered electric vehicle","authors":"Jie Wang, Jianhao Zhou, Wanzhong Zhao","doi":"10.1016/j.geits.2022.100028","DOIUrl":"10.1016/j.geits.2022.100028","url":null,"abstract":"<div><p>Vehicles using a single fuel cell as a power source often have problems such as slow response and inability to recover braking energy. Therefore, the current automobile market is mainly dominated by fuel cell hybrid vehicles. In this study, the fuel cell hybrid commercial vehicle is taken as the research object, and a fuel cell/battery/supercapacitor energy topology is proposed, and an energy management strategy based on a double-delay deep deterministic policy gradient is designed for this topological structure. This strategy takes fuel cell hydrogen consumption, fuel cell life loss, and battery life loss as the optimization goals, in which supercapacitors play the role of coordinating the power output of the fuel cell and the battery, providing more optimization ranges for the optimization of fuel cells and batteries. Compared with the deep deterministic policy gradient strategy (DDPG) and the nonlinear programming algorithm strategy, this strategy has reduced hydrogen consumption level, fuel cell loss level, and battery loss level, which greatly improves the economy and service life of the power system. The proposed EMS is based on the TD3 algorithm in deep reinforcement learning, and simultaneously optimizes a number of indicators, which is beneficial to prolong the service life of the power system.</p></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773153722000287/pdfft?md5=f0f54ab7bed618709547734c6d0a8a3c&pid=1-s2.0-S2773153722000287-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79538569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11