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.

The Combination of Two Control Strategies for Series Hybrid Electric Vehicles

With most countries paying attention to the environment protection, hybrid electric vehicles have become a focus of automobile research and development due to the characteristics of energy saving and low emission. Power follower control strategy(PFCS) and DC-link voltage control strategy are two sorts of control strategies for series hybrid electric vehicles(HEVs). Combining those two control strategies is a new idea for control strategy of series hybrid electric vehicles. By tuning essential parameters which are the defined constants under DClink voltage control and under PFCS, the points of minimum mass of equivalent fuel consumption(EFC) corresponding to a series of variables are marked for worldwide harmonized light vehicles test procedure(WLTP). The fuel economy of series HEVs with the combination control schemes performs better compared with individual control scheme. The results show the effects of the combination control schemes for series HEVs driving in an urban environment.

Series-parallel Hybrid Vehicle Control Strategy Design and Optimization Using Real-valued Genetic Algorithm

Despite the series-parallel hybrid electric vehicle inherits the performance advantages from both series and parallel hybrid electric vehicle, few researches about the series-parallel hybrid electric vehicle have been revealed because of its complex co nstruction and control strategy. In this paper, a series-parallel hybrid electric bus as well as its control strategy is revealed, and a control parameter optimization approach using the real-valued genetic algorithm is proposed. The optimization objective is to minimize the fuel consumption while sustain the battery state of charge, a tangent penalty function of state of charge（SOC） is embodied in the objective function to recast this multi-objective nonlinear optimization problem as a single linear optimization problem. For this strategy, the vehicle operating mode is switched based on the vehicle speed, and an ＂optimal line＂ typed strategy is designed for the parallel control. The optimization parameters include the speed threshold for mode switching, the highest state of charge allowed, the lowest state of charge allowed and the scale factor of the engine optimal torque to the engine maximum torque at a rotational speed. They are optimized through numerical experiments based on real-value genes, arithmetic crossover and mutation operators. The hybrid bus has been evaluated at the Chinese Transit Bus City Driving Cycle via road test, in which a control area network-based monitor system was used to trace the driving schedule. The test result shows that this approach is feasible for the control parameter optimization. This approach can be applied to not only the novel construction presented in this paper, but also other types of 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.

Operation control strategy of series-parallel hydraulic hybrid vehicle

A series-parallel hydraulic hybrid system applied to public buses is put forward,and parameters of key components are analyzed and determined.Energy management strategy based on logic threshold is designed which is aimed at efficient operation of the overall system considering the operational characteristic of the components and taking the curves of engine,hydraulic pump/motor and hydraulic pump as the main design basis;regenerative control strategy which makes regenerative brake system and frictional brake system work harmoniously is designed to raise recovery rate of regenerative brake energy.System dynamic modeling and simulation results show that the energy control strategy designed here is able to adapt system to changes of working condition and switch the operating mode reasonably.The regenerative braking control strategy is effective in raising the utilization of energy and improving fuel economy.

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.

Design and Strategy of Series-Parallel Hybrid System Based on BSFC

In this paper,a drive control strategy is developed based on the characteristics of series-parallel plug-in hybrid system.Energy management strategies in various modes are established with the basis on the minimum brake specific fuel consumption(BSFC)curve of engine.The control strategy,which is based on rules and system efficiency,is adopted to determine the entry/exit mechanisms of various modes according to battery state of charge(SOC),required power and required speed.The vehicle test results verify that the proposed control strategy can improve vehicle economy efficiently and makes a good effect on engine control.

Powertrain design and energy management of a novel coaxial series-parallel plug-in hybrid electric vehicle

For a series plug-in hybrid electric vehicle,higher working efficiency can be achieved by the drive system with two small motors in parallel than that with one big motor alone.However,the overly complex structure will inevitably lead to a substantial increase in the development cost.To improve the system price-performance ratio,a new kind of series-parallel hybrid system evolved from the series plug-in hybrid system is designed.According to the technical parameters of the selected components,the system model is established,and the vehicle dynamic property and pure electric drive economy are evaluated.Based on the dynamic programming,the energy management strategy for the drive system under the city driving cycle is developed,and the superiority validation of the system is completed.For the studied vehicle driven by the designed series-parallel plug-in hybrid system,compared with the one driven by the described series plug-in hybrid system,the dynamic property is significantly improved because of the multi-power coupling,and the fuel consumption is reduced by 11.4%with 10 city driving cycles.In a word,with the flexible configuration of the designed hybrid system and the optimized control strategy of the energy management,the vehicle performance can be obviously improved.

Energy management strategy for a parallel hybrid electric vehicle equipped with a battery/ultra-capacitor hybrid energy storage system

To solve the low power density issue of hybrid electric vehicular batteries, a combination of batteries and ultracapacitors (UCs) could be a solution. The high power density feature of UCs can improve the performance of battery/UC hybrid energy storage systems (HESSs). This paper presents a parallel hybrid electric vehicle (HEV) equipped with an internal combus- tion engine and an HESS. An advanced energy management strategy (EMS), mainly based on fuzzy logic, is proposed to improve the fuel economy of the HEV and the endurance of the HESS. The EMS is capable of determining the ideal distribution of output power among the internal combustion engine, battery, and UC according to the propelling power or regenerative braking power of the vehicle. To validate the effectiveness of the EMS, numerical simulation and experimental validations are carried out. The results indicate that EMS can effectively control the power sources to work within their respective efficient areas. The battery load can be mitigated and prolonged battery life can be expected. The electrical energy consumption in the HESS is reduced by 3.91% compared with that in the battery only system. Fuel consumption of the HEV is reduced by 24.3% compared with that of the same class conventional vehicles under Economic Commission of Europe driving cycle.

Multi-objective parameter optimization for a single-shaft series-parallel plug-in hybrid electric bus using genetic algorithm

最近，插件混合电的公共汽车(PHEB ) 的单个柄的系列平行 powertrain 为驾驶周期由于它的可改变的操作模式，优秀燃料经济和强壮的适应性成为了最流行的 powertrains 之一。为在开发阶段与单个柄的系列平行 powertrain 设置 PHEB，当选择并且匹配主要部件参数时，不过，它仍然比另外的配置面对更大的挑战。由这个问题激发了，全面多目的优化策略与典型 powertrain 为 PHEB 基于基因算法(GA ) 被开发。就公共汽车线路的重覆性和整齐而言，首先，离线的数据处理和数学统计的方法被采用，到获得一个代表性的开车周期，它能很好反映真实世界的公共汽车线路的一般特征。然后，节俭的优化目的被定义，它是由生产关键部件和精力消费的费用组成，并且与动态优化目的结合了，多客观的优化功能被提出。同时， GA 算法被用来优化参数，为新奇系列平行 powertrain 的最佳的部件联合。最后，有原型的比较被执行沿着驾驶周期验证优化 powertrain 的表演。模拟结果显示建议全面多目的优化策略获得的 powertrain 部件的参数可能得到更好的燃料经济，同时保证 PHEB 的动态性能。与原版相对照，费用在 18% 衰退了。因此，策略将为 PHEB 制造商在参数选择上提供理论指导。

串并联混合动力变速箱挡位对整车性能的影响

针对串并联混合动力车辆变速箱选型匹配问题,采用试验设计(DOE)方法选取变速箱最优速比并分析挡位对整车性能的影响。建立了整车仿真模型和控制策略并进行了台架验证,分析了该混合动力系统3种变速箱挡位配置对车辆的加速性能、爬坡性能和整车油耗的影响。仿真结果表明,挡位的增多可以提高整车动力性,降低整车对电池放电功率及电池容量的需求,但是对整车油耗改善较小。进一步仿真结果表明,即使改善发动机低转速中高负荷区域的燃油消耗率,变速箱挡位数对整车油耗的影响也不大。

面向混合动力汽车液压再生能量控制策略研究

针对混合动力汽车制动能量回收控制,提出了一种基于模糊Q学习的液压再生制动系统能量回收效率优化算法。建立了基于并联液压混合动力系统的汽车动力学模型,通过模糊Q学习法对汽车再生制动控制策略进行了优化。在此基础上建立了试验平台,验证液压再生制动仿真模型的准确性。与基于专家经验的模糊控制策略、动态规划算法相比,结果表明,经模糊Q学习算法优化的汽车节能率分别提高了9.62%和8.91%。

基于工况识别的PHEV能量管理策略

为提升并联式混合动力汽车(parallel hybrid electric vehicle,PHEV)的燃油经济性,针对等效燃油消耗最小控制策略(equivalent fuel consumption minimum strategy,ECMS)在不同工况下适应性差的问题,以优化整车等效燃油消耗量为目标,设计基于工况识别算法的变等效因子ECMS能量管理策略。选取3类典型工况建立支持向量机分类模型,通过递归特征消除法对样本特征进行选择,采用鲸鱼算法对支持向量机进行参数优化,使用模拟退火算法分别对3类工况的ECMS等效因子进行离线全局最优求解,并分别存储于等效因子库中,通过训练好的支持向量机分类器对目标优化工况进行工况识别,不同类型的工况片段采用不同的等效因子进行转矩分配。仿真结果显示:相比于逻辑门限能量管理策略,基于工况识别算法的变等效因子ECMS能量管理策略的电池荷电状态(state of charge,SOC)变化量减少8.67%,节油率为13.11%;相比于优化前的ECMS策略电池SOC变化量减少3.47%,节油率约为6.63%。本文提出的基于工况识别算法的变等效因子ECMS能量管理策略可以有效地减少燃油消耗量,提升PHEV的整车经济性。

抗偏移混合拓扑恒流无线充电系统研究

针对电动汽车无线充电系统因偏移导致充电效率降低的实际问题,提出一种新型强抗偏移的恒流无线充电系统。首先,在磁耦合设计上,引入DDQD大解耦线圈有效减缓X、Y两方向偏移耦合系数衰减,通过与DDQ线圈的对比体现所提出的DDQD线圈在抗偏移方面的优越性。然后,在补偿拓扑设计上,通过DDQD线圈将随耦合系数呈不同变化趋势的LCC拓扑和LC拓扑进行串联,使输出功率变化平缓,进一步提高了系统的抗偏移能力,并且使系统具有恒流输出特性。最后,通过仿真实验验证了该方案的有效性,在磁耦合机构发生偏移时,减缓了无线充电系统的线圈耦合系数和传输效率的下降程度,具有一定的现实意义。

串联式混合动力汽车发电机恒压发电性能试验研究

针对串联式混合动力汽车发电机恒压发电性能试验存在的问题,提出一种实际电机负载试验方案,并对发电机进行恒压发电性能试验。结果表明,实际电机负载试验方案切实可行,可为动力单元联合调试提供参考。

基于改进深度强化学习的HEV能量分配策略研究

以并联式混合动力汽车(HEV)为研究对象,建立整车需求功率及动力系统模型,提出一种基于改进深度强化学习(DRL)的能量分配策略。通过改进DRL中的双延迟深度确定性策略梯度(TD3)算法,引入双重回放缓冲区,提出DRB-TD3算法以提升原算法的采样效率。设计了基于规则的约束控制器并嵌入到DRL结构中,以消除不合理的转矩分配。在UDDS行驶工况下,以基于动态规划(DP)的能量分配策略性能作为基准进行仿真实验。实验结果表明,与深度确定性策略梯度(DDPG)算法以及传统TD3算法相比,DRB-TD3算法收敛性能最佳,收敛效率分别提高了61.2%和31.6%;所提出的能量分配策略相比于基于DDPG和基于TD3的能量分配策略,平均燃油消耗分别降低了3.3%和2.3%,燃油经济性达到基于DP的95.2%,效果最佳,且电池荷电状态(SOC)能够保持在一个较好的水平,有助于延长电池的使用寿命。

并联混合动力汽车扭转减振器性能仿真分析

为改善并联混合动力汽车传动系统的扭振特性,开展了扭转减振器的结构及仿真分析研究。对并联混合动力汽车传动系现有扭转减振器进行分析,提出了一种具有新型结构的弧形弹簧式从动盘扭转减振器;针对某款车型建立8自由度集中质量模型,采用AMESim仿真软件搭建仿真模型;通过对离合器从动盘扭转减振器、双质量飞轮和弧形弹簧式从动盘扭转减振器3种不同结构减振器的扭振特性进行仿真对比,分析了它们在典型工况下的扭振特性,并对扭转刚度和迟滞力矩进行了灵敏度分析。结果表明,弧形弹簧式从动盘扭转减振器能保证较短的发动机启动时间,且拥有较好的减振特性;在混合驱动行驶工况下扭转减振器的减振效果与扭转刚度及迟滞力矩的大小呈负相关。

混合动力汽车热管理开发研究

针对某款搭载串并联式混合动力系统的汽车,开展热管理开发及相关研究。文章首先结合混动总成系统热管理参数需求,设计开发了一台热管理系统方案;其次依据热管理关键工况,提取和分析得到了各散热单元的进风量;然后对该方案下的热管理性能进行仿真分析,发现该方案存在高温散热单元和油冷器进风量不足、布局不佳等缺陷,导致高温散热单元和油冷器温度分别高于目标值1.5°C和3.8°C;最后结合风扇和散热单元布局优化等措施,使得高温散热单元和油冷器进风量分别提升了9.37%和8.4%,高温散热单元和油冷器温度分别降低了4°C和4.1°C,达成开发目标。