Modeling and Control of Parallel Hybrid Electric Vehicle Using Sea-Lion Optimization

This paper develops a parallel hybrid electric vehicle(PHEV)propor-tional integral controller with driving cycle.To improve fuel efficiency and reduce hazardous emissions in hybrid electric vehicles(HEVs)combine an electric motor(EM),a battery and an internal combustion engine(ICE).The electric motor assists the engine when accelerating,driving longer highways or climbing hills.This enables the use of a smaller,more efficient engine.It also makes use of the concept of regenerative braking to maximize energy efficiency.In a Hybrid Electric Vehicle(HEV),energy dissipated while braking is utilized to charge the battery.The proportional integral controller was used in this paper to analyze engine,motor performance and the New European Driving Cycle(NEDC)was used in the vehicle driving test using Matlab/Simulink.The proportional integral controllers were designed to track the desired vehicle speed and manage the vehi-cle’s energyflow.The Sea Lion Optimization(SLnO)methods were created to reduce fuel consumption in a parallel hybrid electric vehicle and the results were obtained for the New European Driving Cycle.

Cloud Computing Based Optimal Driving for a Parallel Hybrid Electric Vehicle

A cloud computing based optimal driving method is proposed and its feasibility is validated through a real-world scenario simulation.Based on principles of vehicle dynamics,the driving optimization problem has been formulated into an optimal control problem constrained by traffic rules,directed at achieving lower equivalent fuel consumption and shorter travel time.In order to conveniently specify the constraints and facilitate the application of the dynamic programming(DP)algorithm,the driving optimization problem is transformed into spatial domain and discretized properly.Considering the heavy computational costs of the DP algorithm,a cloud computing based platform structure is proposed to solve the optimal driving problem in real-time.A case study is simulated based on a real-world traffic scenario in Matlab.Simulation results demonstrate that the cloud computing framework is promising toward realizing the real-time energy management for hybrid electric vehicles.

OPTIMAL TORQUE CONTROL STRATEGY FOR PARALLEL HYBRID ELECTRIC VEHICLE WITH AUTOMATIC MECHANICAL TRANSMISSION

In parallel hybrid electrical vehicle （PHEV） equipped with automatic mechanical transmission （AMT）, the driving smoothness and the clutch abrasion are the primary considerations for powertrain control during gearshift and clutch operation. To improve these performance indexes of PHEV, a coordinated control system is proposed through the analyzing of HEV powertrain dynamic characteristics. Using the method of minimum principle, the input torque of transmission is optimized to improve the driving smoothness of vehicle. Using the methods of fuzzy logic and fuzzy-PID, the engaging speed of clutch and the throttle opening of engine are manipulated to ensure the smoothness of clutch engagement and reduce the abrasion of clutch friction plates. The motor provides the difference between the required input torque of transmission and the torque transmitted through clutch plates. Results of simulation and experiments show that the proposed control strategy performs better than the contrastive control system, the smoothness of driving and the abrasion of clutch can be improved simultaneously.

Power Matching and Simulation Analysis of ISG Hybrid Electric Vehicle

Aiming at the limitation of ISG light hybrid electric vehicle, the power matching design of ISG moderate hybrid electric vehicle was studied. According to the requirements of vehicle performance indicators, the parameters of vehicle power drive system including engine, ISG motor, battery and related power transmission system were designed;the basic control strategy of ISG moderate hybrid electric vehicle was put forward;the dynamic model of vehicle was established by using MATLAB/Simulink software platform, and the vehicle performance was simulated under selected cycle conditions. The simulation results show that the parameter matching of the drive system is reasonable, the power performance of the vehicle meets the corresponding requirements, and the fuel economy has been significantly improved.

On Designing of the Main Elements of a Hybrid-Electric Vehicle Driving System

The paper deals with the designing of an electric drive system used for hybrid electric vehicles. The driving system is realized with an induction motor and a voltage source inverter. Specifically, the application is for a series hybrid vehicle powered by electric storage batteries charged by solar batteries. In the first part of the paper the designing of the electric storage batteries and of the photoelectric system is presented. In the second part of the paper some aspects regarding the designing of the induction motor are presented. Then some aspects concerning the voltage source inverter designing are exposed.

A new braking force distribution strategy for electric vehicle based on regenerative braking strength continuity

Regenerative braking was the process of converting the kinetic energy and potential energy, which were stored in the vehicle body when vehicle braked or went downhill, into electrical energy and storing it into battery. The problem on how to distribute braking forces of front wheel and rear wheel for electric vehicles with four-wheel drive was more complex than that for electric vehicles with front-wheel drive or rear-wheel drive. In this work, the frictional braking forces distribution curve of front wheel and rear wheel is determined by optimizing the braking force distribution curve of hydraulic proportional-adjustable valve, and then the safety brake range is obtained correspondingly. A new braking force distribution strategy based on regenerative braking strength continuity is proposed to solve the braking force distribution problem for electric vehicles with four-wheel drive. Highway fuel economy test(HWFET) driving condition is used to provide the speed signals, the braking force equations of front wheel and rear wheel are expressed with linear equations. The feasibility, effectiveness, and practicality of the new braking force distribution strategy based on regenerative braking strength continuity are verified by regenerative braking strength simulation curve and braking force distribution simulation curves of front wheel and rear wheel. The proposed strategy is simple in structure, easy to be implemented and worthy being spread.

City-Bus-Route Demand-based Efficient Coupling Driving Control for Parallel Plug-in Hybrid Electric Bus

Recently,plug?in hybrid electric bus has been one of the energy?e cient solutions for urban transportation. However,the current vehicle e ciency is far from optimum,because the unpredicted external driving conditions are di cult to be obtained in advance. How to further explore its fuel?saving potential under the complicated city bus driving cycles through an e cient control strategy is still a hot research issue in both academic and engineering area. To realize an e cient coupling driving operation of the hybrid powertrain,a novel coupling driving control strategy for plug?in hybrid electric bus is presented. Combined with the typical feature of a city?bus?route,the fuzzy logic inference is employed to quantify the driving intention,and then to determine the coupling driving mode and the gear?shifting strategy. Considering the response deviation problem in the execution layer,an adaptive robust controller for electric machine is designed to respond to the transient torque demand,and instantaneously compensate the response delay and the engine torque fluctuation. The simulations and hard?in?loop tests with the actual data of two typical driving conditions from the real?world city?bus?route are carried out,and the results demonstrate that the pro?posed method could guarantee the hybrid powertrain to track the actual torque demand with 10.4% fuel economy improvement. The optimal fuel economy can be obtained through the optimal combination of working modes. The fuel economy of plug?in hybrid electric bus can be significantly improved by the proposed control scheme without loss of drivability.

考虑驾驶风格的混合动力汽车强化学习能量管理策略

为了提升混合动力汽车能量管理策略对不同风格驾驶员的适应性,基于深度强化学习和等效燃油消耗最小策略(equivalent consumption minimization strategy,ECMS),提出一种考虑驾驶风格的混合动力汽车能量管理策略。通过实车试验采集驾驶员行驶数据,基于采集数据进行驾驶员驾驶风格的聚类分析,建立驾驶风格识别模型;构建基于强化学习和ECMS的能量管理策略,将驾驶风格系数作为强化学习状态变量,利用多种驾驶风格的组合工况训练深度确定性策略梯度智能体,获取不同工况和驾驶风格下ECMS等效因子,采用ECMS求解最优发动机、电机转矩分配以及变速箱挡位;搭建硬件在环测试平台,并基于实际采集的不同驾驶员驾驶数据构建测试工况,验证所提出控制策略的有效性。研究结果表明,相较于基于规则策略、基于等效因子比例修正的自适应ECMS以及DRL-SAC策略,提出的考虑驾驶风格的强化学习能量管理策略使整车能量消耗分别降低16.35%、11.11%和7.56%,所提控制策略的有效性得到了验证。

Driving-Cycle-Aware Energy Management of Hybrid Electric Vehicles Using a Three-Dimensional Markov Chain Model

This study developed a new online driving cycle prediction method for hybrid electric vehicles based on a three-dimensional stochastic Markov chain model and applied the method to a driving-cycle-aware energy management strategy.The impacts of different prediction time lengths on driving cycle generation were explored.The results indicate that the original driving cycle is compressed by 50%,which significantly reduces the computational burden while having only a slight effect on the prediction performance.The developed driving cycle prediction method was implemented in a real-time energy management algorithm with a hybrid electric vehicle powertrain model,and the model was verified by simulation using two different testing scenarios.The testing results demonstrate that the developed driving cycle prediction method is able to efficiently predict future driving tasks,and it can be successfully used for the energy management of hybrid electric vehicles.

Real-time energy-efficient anticipative driving control of connected and automated hybrid electric vehicles

In this paper,we propose a real-time energy-efficient anticipative driving control strategy for connected and automated hybrid electric vehicles(HEVs).Considering the inherent complexities brought about by the velocity profile optimization and energy management control,a hierarchical control architecture in the model predictive control(MPC)framework is developed for real-time implementation.In the higher level controller,a novel velocity optimization problem is proposed to realize safe and energy-efficient anticipative driving.The real-time control actions are derived through a computationally efficient algorithm.In the lower level controller,an explicit solution of the optimal torque split ratio and gear shift schedule is introduced for following the optimal velocity profile obtained from the higher level controller.The comparative simulation results demonstrate that the proposed strategy can achieve approximately 13%fuel consumption saving compared with a benchmark strategy.

基于混合粒子群的电动汽车转矩分配策略研究

针对双电机驱动系统电动汽车前、后轴电机转矩分配问题,利用Simulink与AVL-Cruise软件建立了双电机电动汽车整车模型;基于车辆构型特点建立双电机驱动系统效率数学模型,以双电机驱动系统的整体效率最高为优化目标,在前、后轴电机特性约束范围内通过混合粒子群算法,对转矩分配系数进行迭代优化研究。仿真结果表明,在单个工况点和连续运行工况下,混合粒子群算法的转矩分配策略能够实现合理的转矩分配满足车辆行驶的需求,在NEDC、CLTC-P、WLTC三种循环工况下,采用该策略的电动汽车续驶里程延长了11.71%、9.06%、9.46%,双电机电动汽车的经济性明显提升。

电动汽车电驱动系统抗干扰扭振自适应控制研究

为了提高电动汽车处于纯电动模式下工作效率,设计了一种电动汽车电驱动系统抗干自适应扰扭振控制策略。构建电驱动系统动力平衡方程,同时引入了前馈与反馈控制器进行系统调控。有干扰仿真结果表明:设置前馈控制后,电动汽车启动阶段存在外部干扰因素影响时,可通过反馈控制器减缓传动部件产生的振动作用,从而达到更平稳控制效果,实现乘坐舒适度的显著改善。该研究能够有效消除电动汽车电驱动系统抗干扰能力,具有很好的应用价值。

某混合动力车型低温纯电续航能耗分解

文章通过对一款混合动力汽车在环境温度25℃、-7℃和-18℃三种温度下进行纯电续航仿真和实测,对比分析了动力电池放电功率点、PTC功耗、DCDC功耗和驱动电机效率差异,结果表明:环境温度-7℃比25℃模拟用户实际工况电耗上升7.4kW·h,-18℃比25℃电耗上升8.3kW·h,低温环境下PTC功耗、DCDC功耗增大,电机效率降低;客户续航感受越差。

An enhanced eco-driving strategy based on reinforcement learning for connected electric vehicles:cooperative velocity and lane-changing control

Purpose–This study aims to propose an enhanced eco-driving strategy based on reinforcement learning(RL)to alleviate the mileage anxiety of electric vehicles(EVs)in the connected environment.Design/methodology/approach–In this paper,an enhanced eco-driving control strategy based on an advanced RL algorithm in hybrid action space(EEDC-HRL)is proposed for connected EVs.The EEDC-HRL simultaneously controls longitudinal velocity and lateral lane-changing maneuvers to achieve more potential eco-driving.Moreover,this study redesigns an all-purpose and efficient-training reward function with the aim to achieve energy-saving on the premise of ensuring other driving performance.Findings–To illustrate the performance for the EEDC-HRL,the controlled EV was trained and tested in various traffic flow states.The experimental results demonstrate that the proposed technique can effectively improve energy efficiency,without sacrificing travel efficiency,comfort,safety and lane-changing performance in different traffic flow states.Originality/value–In light of the aforementioned discussion,the contributions of this paper are two-fold.An enhanced eco-driving strategy based an advanced RL algorithm in hybrid action space(EEDC-HRL)is proposed to jointly optimize longitudinal velocity and lateral lane-changing for connected EVs.A full-scale reward function consisting of multiple sub-rewards with a safety control constraint is redesigned to achieve eco-driving while ensuring other driving performance.

Critical Speeds of Electric Vehicles for Regenerative Braking

Efficient regenerative braking of electric vehicles(EVs)can enhance the efficiency of an energy storage system(ESS)and reduce the system cost.To ensure swift braking energy recovery,it is paramount to know the upper limit of the regenerative energy during braking.Therefore,this paper,based on 14 typical urban driving cycles,proposes the concept and principle of confidence interval of“probability event”and“likelihood energy”proportion of braking.The critical speeds of EVs for braking energy recovery are defined and studied through case studies.First,high-probability critical braking speed and high-energy critical braking speed are obtained,compared,and analyzed,according to statistical analysis and calculations of the braking randomness and likelihood energy in the urban driving cycles of EVs.Subsequently,a new optimized ESS concept is proposed under the frame of a battery/ultra-capacitor(UC)hybrid energy storage system(HESS)combined with two critical speeds.The battery/UC HESS with 9 UCs can achieve better regenerative braking performances and discharging performances,which indicates that a minimal amount of UCs can be used as auxiliary power source to optimize the ESS.After that,the efficiency regenerative braking model,including the longitudinal dynamics,motor,drivetrain,tire,and wheel slip models,is established.Finally,parameters optimization and performance verification of the optimized HESS are implemented and analyzed using a specific EV.Research results emphasize the significance of the critical speeds of EVs for regenerative braking.

混动汽车的工况自适应等效燃油消耗最小控制

为了减小混合动力汽车的燃油消耗,提出了驾驶工况自适应的等效燃油消耗最小控制策略。介绍了混合动力系统结构和工作模式,建立了混合动力车辆的实时控制模型。基于庞特里亚金极小值原理和等效燃油消耗最小策略求解了车辆在多个优化目标下的最优控制律;提取了车辆行驶工况特征参数,使用学习矢量量化神经网络构造了驾驶工况智能识别器,实现了驾驶工况精准识别。为了使等效燃油消耗最小策略适用于复杂多变的驾驶工况,提出了等效因子随驾驶工况自适应变化策略。使用由4种标准工况组成的综合工况进行仿真验证,并与文献[6]的智能规则控制、文献[11]的模型预测控制策略进行比较,这里提出的自适应等效燃油消耗最小策略的百公里油耗比智能规则控制减少了7.64%,比模型预测控制减少了4.96%,说明了自适应等效燃油消耗最小策略可以有效减少混合动力汽车的燃油消耗。

车-路-云融合的智能混合动力汽车节能驾驶技术研究进展与挑战

随着汽车的智能化与网联化,混合动力汽车的节能驾驶技术已由单纯的动力总成能量管理向涵盖车-路-云一体化的综合控制演化,基于车速规划的经济性驾驶与基于路径规划的经济性路由可显著提高汽车的节油率。介绍了现有混合动力汽车的典型节能驾驶技术,指出了节能驾驶技术的商业价值及其节油潜力;归纳总结了经济性驾驶的研究现状,引出了路径规划对于能耗的重要影响;从能耗模型构建、路径优化问题建立和求解算法三方面系统梳理了经济性路由的研究现状,指明了其研究思路;探究讨论了多车混合经济性路由问题,为物流配送车辆的经济性调度提供了优化思路;对混合动力汽车节能驾驶技术的发展趋势进行展望。

基于分层式控制的混合动力汽车生态驾驶研究

智能交通系统技术的发展为进一步提高车辆驾驶性能带来了新的机遇。插电式混合动力汽车的生态驾驶涉及到3个问题,分别为如何利用动态交通信息对纵向行驶速度进行规划,动力电池SOC全局最优快速规划,以及动力系统实时能量管理。为此,本文中设计了一种结合通精度模型的兼顾计算效率与求解精度的分层式控制策略。上层控制融合了动态交通信号灯信息,通过对车辆行驶速度优化提高了驾驶舒适性,中层则通过对动力系统模型拟合近似,利用凸优化算法实现了SOC快速全局最优规划,为消除拟合模型产生的误差,下层则基于原始非线性模型,通过反馈控制,构建了一种自适应等效燃油消耗最小值策略(A-ECMS)。结果表明,车辆的驾驶舒适性相比于没有速度优化的策略提升了75.92%,且燃油经济性相比于两种常用的基于线性规划的策略分别提升了7.39%与10.91%。

某PHEV动力电池的行车加热特性研究

为了提升某插电式混合动力车(PHEV)动力电池在低温环境下的充放电功率限值以改善能量回收利用率和行车换挡平顺性,提出了将发动机冷却液作为热源对低温电池进行加热和利用正温度系数(PTC)加热片生热提供热源加热电池的两种加热方案。基于流动和传热学理论借助数值计算方法,建立了两种加热方案在高荷电状态(SOC)的电量消耗(CD)工况和低荷电状态的电量维持(CS)工况下的数值计算模型。结合整车冬季测试的数据对计算模型的准确性进行了验证,并借助验证后的计算模型对两种低温加热方式带来的充放电功率限值的提升进行了分析计算。结果表明:电量消耗(CD)工况下,发动机冷却液和正温度系数(PTC)加热片加热30 min对于电芯最低温度升至5℃缩短时长分别为9 min和10 min,对于充电功率的提升分别为23 kW和17.5 kW,对于放电功率的提升分别为24 kW和20.7 kW;电量维持(CS)工况下,两种加热方式加热30 min对于电芯最低温度升至-10℃缩短时长为45 min和36 min,充电功率的提升分别为31 kW和6.91 kW,对于放电功率的提升分别为13 kW和13.8 kW。因此,采取加热能使电池较快升温,能使充放电功率限制迅速增加。采用发动机冷却液加热比使用正温度系数(PTC)加热片加热更快达到目标温度,同时对于充放电功率限值的提升量也更加明显,能带来更加平顺的换挡性能和较高的能量回收利用率。

环境温度对混合动力汽车实际道路行驶油耗的影响研究

为探究环境温度对混合动力汽车油耗的影响程度,选取不同技术路线的4辆混合动力汽车进行了不同温度下的多次实际道路行驶油耗测试,结果表明,插电式混合动力汽车(PHEV)和增程式混合动力汽车在实际道路行驶时的油耗结果明显高于试验室油耗测试结果,不可外部充电式混合动力汽车(NOVC-HEV)及PHEV在高温、低温环境下油耗均会出现明显上升,故常温条件下全球统一轻型车辆测试循环(WLTC)工况油耗测试结果不能准确反映NOVC-HEV、增程式混合动力汽车和PHEV车型的真实油耗水平,环境温度是影响混合动力汽车油耗表现的重要因素。