OPTIMIZATION APPROACH FOR HYBRID ELECTRIC VEHICLE POWERTRAIN DESIGN

According to bench test results of fuel economy and engine emission for thereal power-train system of EQ7200HEV car. a 3-D performance map oriented quasi-linear model isdeveloped for the configuration of the powertrain components such as internal combustion engine,traction electric motor, transmission, main retarder and energy storage unit. A genetic algorithmbased on optimization procedure is proposed and applied for parametric optimization of the keycomponents by consideration of requirements of some driving cycles. Through comparison of numericalresults obtained by the genetic algorithm with those by traditional optimization methods, it isshown that the present approach is quite effective and efficient in emission reduction and fueleconomy for the design of the hybrid electric car powertrain.

Synthetical Efficiency-based Optimization for the Power Distribution of Power-split Hybrid Electric Vehicles

Now the optimization strategies for power distribution are researched widely, and most of them are aiming to the optimal fuel economy and the driving cycle must be preknown. Thus if the actual driving condition deviates from the scheduled driving cycle, the effect of optimal results will be declined greatly. Therefore, the instantaneous optimization strategy carried out on-line is studied in this paper. The power split path and the transmission efficiency are analyzed based on a special power-split scheme and the efficiency models of the power transmitting components are established. The synthetical efficiency optimization model is established for enhancing the transmission efficiency and the fuel economy. The identification of the synthetical efficiency as the optimization objective and the constrain group are discussed emphatically. The optimization is calculated by the adaptive simulated annealing （ASA） algorithm and realized on-line by the radial basis function （RBF）-based similar models. The optimization for power distribution of the hybrid vehicle in an actual driving condition is carried out and the road test results are presented. The test results indicate that the synthetical efficiency optimization method can enhance the transmission efficiency and the fuel economy of the power-split hybrid electric vehicle （HEV） observably. Compared to the rules-based strategy the optimization strategy is optimal and achieves the approximate global optimization solution for the power distribution. The synthetical efficiency optimization solved by ASA algorithm can give attentions to both optimization quality and calculation efficiency, thus it has good application foreground for the power distribution of power-split HEV.

Parameters matching and optimization of parallel hybrid electric vehicle powertrain

Aiming at the development of parallel hybrid electric vehicle （PHEV） powertrain, parameter matching and optimization are presented, According to the performance of PHEV, the optimization range of engine, motor, driveline gear ratio and battery parameters are determined. And then a two-level optimization problem is formulated based on analytical target cascading （ATC）. At the system level, the optimization of the whole vehicle fuel economy is carried out, while the tractive performance is defined as the constraints. The optimized parameters are cascaded to the subsystem as the optimization targets. At the subsystem level, the final drive and transmission design are optimized to make the ratios as close to the targets as possible. The optimization result shows that the fuel economy had improved significantly, while the tractive performance maintains the former level.

Powertrain Fuel Consumption Modeling and Benchmark Analysis of a Parallel P4 Hybrid Electric Vehicle Using Dynamic Programming

The goal of this work is to develop a hybrid electric vehicle model that is suitable for use in a dynamic programming algorithm that provides the benchmark for optimal control of the hybrid powertrain. The benchmark analysis employs dynamic programming by backward induction to determine the globally optimal solution by solving the energy management problem starting at the final timestep and proceeding backwards in time. This method requires the development of a backwards facing model that propagates the wheel speed of the vehicle for the given drive cycle through the driveline components to determine the operating points of the powertrain. Although dynamic programming only searches the solution space within the feasible regions of operation, the benchmarking model must be solved for every admissible state at every timestep leading to strict requirements for runtime and memory. The backward facing model employs the quasi-static assumption of powertrain operation to reduce the fidelity of the model to accommodate these requirements. Verification and validation testing of the dynamic programming algorithm is conducted to ensure successful operation of the algorithm and to assess the validity of the determined control policy against a high-fidelity forward-facing vehicle model with a percent difference of fuel consumption of 1.2%. The benchmark analysis is conducted over multiple drive cycles to determine the optimal control policy that provides a benchmark for real-time algorithm development and determines control trends that can be used to improve existing algorithms. The optimal combined charge sustaining fuel economy of the vehicle is determined by the dynamic programming algorithm to be 32.99 MPG, a 52.6% increase over the stock 3.6 L 2019 Chevrolet Blazer.

Fuel Saving and Control for Hybrid Electric Powertrains

This paper focuses on comparing the performance of the embedded control of a hybrid powertrain with the original and downsized engine. The main idea is to store the normally wasted mechanical regenerative energy in energy storage devices for later usage. The regenerative energy recovery opportunity exists in any condition where the speed of motion is in the opposite direction to the applied force or torque. A rule based optimal robust control algorithm is developed and is tuned for different work cycles. A comparison of the fuel savings using the hybrid system with the original and downsized engines is performed.

Performance and Stability of Supercapacitor Modules based on Porous Carbon Electrodes in Hybrid Powertrain

Hybrid power sources have attracted much attention in the electric vehicle area. Particularly, electric-electric hybrid powertrain system consisting of supercapacitor modules and lithium-ion batteries has been widely applied because of the high power density of supercapacitors. In this study, we design a hybrid powertrain system containing two porous carbon electrode-based supercapacitor modules in parallel and one lithium ion battery pack. With the construction of the testing station, the performance and stability of the used supercapacitor modules are investigated in correlation with the structure of the supercapacitor and the nature of the electrode materials applied. It has been shown that the responding time for voltage vibration from 20 V to 48.5 V during charging or discharging process decreases from about 490 s to 94 s with the increase in applied current from 20 A to 100 A. The capacitance of the capacitor modules is nearly independent on the applied current. With the designed setup, the energy efficiency can reach as high as 0.99. The results described here provide a guidance for material selection of supercapacitors and optimized controlling strategy for hybrid power system applied in electric vehicles.

中国混合动力汽车动力总成技术进展

在国家政策与市场需求的双重驱动下,2021年以来,中国品牌混合动力汽车动力总成技术实现突破,围绕中国市场特点与消费者用车习惯推出一批具有中国特色、世界范围内领先的混合动力汽车产品。近期混合动力汽车市场销量呈爆发式增长,2023年中国市场混合动力乘用车销售超300万辆,同比增长83%。然而,受近年来汽车领域电动化浪潮影响,行业内尚存关于混合动力汽车仅为过渡性技术的观点,部分消费者对国产混动汽车技术产品力仍存质疑。为纠正对混合动力汽车的片面性、偏见性认识,该文围绕中国混合动力汽车动力总成技术路线展开,聚焦多样化的混动架构与专用化的核心部件,提出新的混合度定义作为动力总成电气化程度的统一评价标准,探讨国内外主流混动技术异同,剖析当下中国最前沿的混动技术特点与发展趋势,厘清中国混动汽车动力总成的发展脉络。研究表明:中国式混动汽车以大容量动力电池与插电式混合动力为技术特色,实现发动机、电机两大驱动动力源以及动力电池、增程系统两大动力能量源的灵活混合与优势互补。与纯内燃机车相比,得益于电驱动技术辅助,混合动力汽车聚焦提高发动机热效率、发动机高效区利用率以及整车燃油经济性。与纯电动车相比,混合动力汽车则基于发动机的增程发电,以高性价比和高便利度解决纯电动车的补能焦虑;并通过结合发动机直驱、变速器动力放大等机械驱动技术,以更低的硬件成本实现更稳定的强劲动力输出。混合动力汽车的独特优势使其作为长期性技术路线,将成为带动汽车产业向碳中和方向转型升级的关键,该文对当下市场的深度分析和未来趋势的理性推测将为中国混动技术的进一步发展提供有益参考。

轻卡用混合动力总成技术发展现状与趋势

在环境污染、能源安全以及产业自主可控等多重压力下,发展新能源汽车势在必行。目前商用车混合动力产品不成熟,且各家技术路线有所不同。文章从构型、技术特点、应用场景等方面对轻卡用混合动力总成技术发展现状进行了剖析,并阐述了未来发展的趋势,以指导主机厂进行动力总成选型以及整车匹配,更好促进我国新能源汽车可持续发展。

电液混合动力系统关键技术及能量管理研究综述

现有混合动力驱动技术以油电、油液混合动力为主,旨在提高传统燃油车辆的能量利用率、降低油耗和排放.基于液压技术的大功率密度及能量再生优势,电液混合动力系统可在全速工况范围内实现能量高效利用,提高纯电驱系统的功率密度,有效改善电动车辆续驶里程及蓄电池循环使用寿命.本文对电液混合动力系统构型、能量回收技术、能量释放模式及控制策略等相关研究成果的进展、现状及发展趋势进行综述,分析了利用电液混合动力构型与先进能量管理策略提升纯电动车辆动力性能与能量利用率的可行性技术方案与应用前景.根据已有研究成果,装备电液混合动力系统后车辆最大可降低约40%的能量消耗,在能量高效利用方面具有显著优势.对于电液混合动力系统而言,液压能再生、耦合与释放等与行驶场景及电机工况点密切相关,研究重点应解决动力耦合、再生制动与能量管理等关键技术,从而提升动力系统的综合性能特别是功率密度与节能特性.

燃料电池汽车动力系统及能量管理策略研究进展

动力系统是燃料电池汽车(FCV)的核心,可分为单一式系统与混合动力系统两大类,其中,将燃料电池与辅助电源相结合组成“电-电”混合动力系统,已成为业界主流。本文根据辅助电源类型的不同,提出3类FCV混动系统的构建方案,分别为燃料电池+动力电池方案、燃料电池+超级电容方案、燃料电池+动力电池+超级电容方案,并对各方案的优势和劣势进行比较。同时,本文综述了近年来国内外学者提出的面向FCV的代表性能量管理策略,从理论基础与求解方法的差异出发,将现有燃料电池汽车的能量管理策略分为3类:基于规则定义的策略、基于最优化方法的策略以及基于机器学习的策略,并总结了各类策略在最优性与实时性等方面的优势和劣势。其中,基于规则定义的策略最易实现,在工程应用中最为普遍,但无法实现性能最优;基于最优化方法的策略能够接近甚至达到理论最优,但存在计算量过大、计算耗时过长、实时性差等问题;以强化学习为代表的基于机器学习的策略有望在最优性与实时性之间实现理想的平衡,但目前还存在模型训练耗时长、试错代价高等困难,在实车应用层面还存在一定挑战。基于文献研究与分析,本文提出以下观点:1)以大功率燃料电池为核心的功率混合型系统是FCV混动系统的未来发展方向;2)必须进一步提升智能化程度,根据实际使用场景开发具有个性化的能量管理策略;3)亟需建立关于燃料电池汽车能量管理策略的综合评价体系。

船舶多堆燃料电池混合动力系统能量管理策略优化

为研究多堆燃料电池系统(MFCS)、锂电池为动力源的船舶混合动力系统的能量管理策略(EMS),本文提出一种基于粒子群优化(PSO)算法的多级功率分配策略。首先,利用一级EMS分析MFCS和锂电池需求功率,其次,构建以MFCS总效率为优化目标的二级MFCS协同控制策略,优化燃料电池之间的功率分配。最后,基于燃料电池混合动力船舶典型工况,分析船舶混合动力系统的功率分布、等效氢耗量及燃料电池系统效率、加减载速率。研究结果表明,与等效氢消耗最小化策略(ECMS)相比,该策略下的燃料电池1和燃料电池2的氢耗量分别降低了15%和23%,MFCS总效率提高了1.15%,且燃料电池的功率变化波动更小。该研究有助于提高混合动力系统中燃料电池的经济性和耐久性。

小型全电/混动飞机技术路线与动力系统综述

该文对小型全电/混动载人飞机的技术发展路线、航空推进电机、动力系统架构进行分析、总结与展望。首先,从载人飞机的气动布局、结构拓扑、动力源和起降形式等方面分析,分出6条技术路线,总结各自的乘客数、最大起飞重量、巡航速度、功率和航程等技术指标。其次,总结已装机或拟装机航空推进电机的技术参数和应用机型。对先进航空推进电机的发展现状,按功率等级分类探讨了三相永磁电机、多相永磁电机、兆瓦级涡轮机驱动的兆瓦级电机/发电机、高温超导电机。最后,对6种动力系统架构的技术路线特点、关键技术进行梳理,分析载人全电/混动飞机未来的发展方向。国内载人电动/混动飞机领域刚起步,该文的研究工作对飞机的总体气动布局设计、功率需求、器件选型、动力系统设计具有重要的参考价值。

双行星排混合动力客车动态规划能量管理策略研究

为解决混合动力系统传统动态规划(Dynamic Programming,DP)策略成本函数值受罚函数影响较大、平衡电量调试时间较长的问题,针对某款双行星排混合动力客车提出了变惩罚系数DP(Variable Penalty Coefficient DP,DP-VAR)策略和边界迭代DP(Boundary Iterative DP,DP-ITE)策略。同时,还提出了基于XGBoost算法的动态规划策略模式切换规则提取方法,并对自适应等效燃油消耗最小策略(Adaptive Equivalent Fuel Consumption Minimization Strategy,A-ECMS)进行了改进,建立了具有模式切换规则的A-ECMS策略。基于C-WTVC工况的仿真结果表明:(1)相比于DP策略,DPVAR和DP-ITE策略的控制规则更为明确且百公里油耗分别降低了1.18%和4.31%;(2)DP-ITE策略在取消罚函数的前提下具有终止SOC绝对收敛性;(3)优化后的A-ECMS策略较优化前的百公里油耗降低了1.17%。

基于多智能体强化学习的重载运输车队队列控制

重载运输队列作为现代战争战备物资高效运输方式,有效提升运输能力并降低运输成本。现有队列控制主要关注运动控制特征,忽略了重载特种车辆自身驱动系统构型下系统动力响应特性。基于此,提出了基于多智能体强化学习的重载运输车队队列控制策略,通过控制策略自主式参数优化实现重载队列协同控制,搭建了融合长短时记忆网络的柔性动力需求引导方法,将长期规划策略与短期控制策略解耦,并分别在双层马尔科夫链迭代,建立动力总成元件工况柔性调节控制方法。标准工况试验结果表明:所提出的队列控制策略使队列行驶过程中车头时距保持在1.2 s,动力电池荷电状态维持在35%~65%,并使发动机工作在高效经济区间内,有效提升了重载运输队列的稳定性、耐久性与燃油经济性。

混合动力汽车发动机启停工况扭振自适应模糊控制

混合动力汽车(hybrid electric vehicle,HEV)发动机启停过程伴随的转矩脉动,易诱发车辆传动系扭振,导致车辆动力不平顺。为解决上述问题,提出并验证基于电磁阻尼自适应模糊控制的传动系扭振主动控制方法。建立行星混联式混合动力汽车发动机启停工况动力学仿真模型和发动机启停控制逻辑,提出发动机启停扭振自适应模糊控制策略,开展2种运行状态下发动机启停工况仿真,对比分析无控制和自适应模糊控制下传动系扭转振动响应曲线。结果表明,自适应模糊控制相比无控制状态:定置停车时发动机启动和停机工况扭振平均衰减率分别为23.8%和30.1%,车辆行进间发动机启动和停机工况扭振平均衰减率分别为12.1%和23.6%。该方法可有效衰减发动机启停工况传动系扭转振动,提升混合动力汽车发动机启停工况NVH(noise,vibration,and harshness)性能。

混合动力汽车动力系统功能分析及仿真研究

在混合动力设计开发前期,利用仿真软件对混合动力系统进行性能仿真和深入研究。通过阐述混合动力汽车动力系统的构型方案,分析了混合动力汽车的动力系统功能、驾驶操作模式以及控制策略。基于AVL CRUISE仿真软件,搭建了某款混合动力汽车的整车及动力系统仿真模型,并进行了整车动力性和经济性的仿真验证。仿真结果表明,混合动力车型性能和功能满足设计要求,为混合动力系统样车试验研究奠定基础。

基于效率最优的混动汽车功率分流控制方法

为了提高混动车辆的燃油经济性,提出一种效率分析方法,通过确定车辆在不同工况点的发动机燃油消耗和电池荷电状态的关系,将电池功率折算成等效里程,以每一工况点的综合里程最长为目标,来计算系统在不同模式下不同工况点的最优效率,并寻优得出各模式下的最优效率图谱以及对应的扭矩分配或功率分流图谱,应用于实车控制策略,缩减标定开发周期。试验表明,电池荷电状态在预定范围内保持平衡,发动机运行工作点分布于高效区域内,能有效提高混动控制的实时性和整车燃油经济性,减少系统能量损失。该方法可以离线计算,不依赖于工程经验,为整车标定开发提供理论参考,大大缩减标定开发周期,降低成本,且应用于整车策略中实时性好。

Power-balancing Instantaneous Optimization Energy Management for a Novel Series-parallel Hybrid Electric Bus

Energy management（EM） is a core technique of hybrid electric bus（HEB） in order to advance fuel economy performance optimization and is unique for the corresponding configuration. There are existing algorithms of control strategy seldom take battery power management into account with international combustion engine power management. In this paper, a type of power-balancing instantaneous optimization（PBIO） energy management control strategy is proposed for a novel series-parallel hybrid electric bus. According to the characteristic of the novel series-parallel architecture, the switching boundary condition between series and parallel mode as well as the control rules of the power-balancing strategy are developed. The equivalent fuel model of battery is implemented and combined with the fuel of engine to constitute the objective function which is to minimize the fuel consumption at each sampled time and to coordinate the power distribution in real-time between the engine and battery. To validate the proposed strategy effective and reasonable, a forward model is built based on Matlab/Simulink for the simulation and the dSPACE autobox is applied to act as a controller for hardware in-the-loop integrated with bench test. Both the results of simulation and hardware-in-the-loop demonstrate that the proposed strategy not only enable to sustain the battery SOC within its operational range and keep the engine operation point locating the peak efficiency region, but also the fuel economy of series-parallel hybrid electric bus（SPHEB） dramatically advanced up to 30.73% via comparing with the prototype bus and a similar improvement for PBIO strategy relative to rule-based strategy, the reduction of fuel consumption is up to 12.38%. The proposed research ensures the algorithm of PBIO is real-time applicability, improves the efficiency of SPHEB system, as well as suite to complicated configuration perfectly.

ENERGY MANAGEMENT STRATEGY FOR PARALLEL HYBRID ELECTRIC VEHICLES

Energy management strategy (EMS) is the core of the real-time controlalgorithm of the hybrid electric vehicle (HEV). A novel EMS using the logic threshold approach withincorporation of a stand-by optimization algorithm is proposed. The aim of it is to minimize theengine fuel consumption and maintain the battery state of charge (SOC) in its operation range, whilesatisfying the vehicle performance and drivability requirements. The hybrid powertrain bench testis carried out to collect data of the engine, motor and battery pack, which are used in the EMS tocontrol the powertrain. Computer simulation model of the HEV is established in the MATLAB/Simulinkenvironment according to the bench test results. Simulation results are presented for behaviors ofthe engine, motor and battery. The proposed EMS is implemented for a real parallel hybrid carcontrol system and validated by vehicle field tests.

Toward More Electric Powertrains in Aircraft:Technical Challenges and Advancements

The main purpose of this article is to provide an instructive review of the technological challenges hindering the road toward more electric powertrains in aircraft.Hybrid,all-electric,and turboelectric powertrain architectures are discussed as possible fuel consumption and weight reduction solutions.Among these architectures,the short-term implementation of hybrid and all-electric architectures is limited,particularly for large-capacity aircraft due to the low energy/power density levels achievable by state-of-the-art electrical energy storage systems.Conversely,turboelectric architectures with advanced distributed propulsion and boundary layer ingestion are set to lead the efforts toward more electric powertrains.At the center of this transition,power converters and high-power density electric machines,i.e.,electric motors and generators,and their corresponding thermal management systems are analyzed as the key devices enabling the more electric powertrain.Moreover,to further increase the fuel efficiency and power density of the aircraft,the benefits and challenges of implementing higher voltage powertrains are described.Lastly,based on the findings collected in this article,the projected roadmap toward more electric aircraft powertrains is presented.Herein,the individual targets for each technology,i.e.,batteries,electric machines,and power converters,and how they translate to future aircraft prototypes are illustrated.