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.

Estimation Method of State-of-Charge For Lithium-ion Battery Used in Hybrid Electric Vehicles Based on Variable Structure Extended Kalman Filter

Since the main power source of hybrid electric vehicle（HEV） is supplied by the power battery,the predicted performance of power battery,especially the state-of-charge（SOC） estimation has attracted great attention in the area of HEV.However,the value of SOC estimation could not be greatly precise so that the running performance of HEV is greatly affected.A variable structure extended kalman filter（VSEKF）-based estimation method,which could be used to analyze the SOC of lithium-ion battery in the fixed driving condition,is presented.First,the general lower-order battery equivalent circuit model（GLM）,which includes column accumulation model,open circuit voltage model and the SOC output model,is established,and the off-line and online model parameters are calculated with hybrid pulse power characteristics（HPPC） test data.Next,a VSEKF estimation method of SOC,which integrates the ampere-hour（Ah） integration method and the extended Kalman filter（EKF） method,is executed with different adaptive weighting coefficients,which are determined according to the different values of open-circuit voltage obtained in the corresponding charging or discharging processes.According to the experimental analysis,the faster convergence speed and more accurate simulating results could be obtained using the VSEKF method in the running performance of HEV.The error rate of SOC estimation with the VSEKF method is focused in the range of 5% to 10% comparing with the range of 20% to 30% using the EKF method and the Ah integration method.In Summary,the accuracy of the SOC estimation in the lithium-ion battery cell and the pack of lithium-ion battery system,which is obtained utilizing the VSEKF method has been significantly improved comparing with the Ah integration method and the EKF method.The VSEKF method utilizing in the SOC estimation in the lithium-ion pack of HEV can be widely used in practical driving conditions.

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.

Simulation research of energy management strategy for dual mode plug-in hybrid electrical vehicles

In this paper, a plug-in hybrid electrical vehicle(PHEV) is taken as the research object, and its dynamic performance and economic performance are taken as the research goals. Battery charge-sustaining(CS) period is divided into power mode and economy mode. Energy management strategy designing methods of power mode and economy mode are proposed. Maximum velocity, acceleration performance and fuel consumption are simulated during the CS period in the AVL CRUISE simulation environment. The simulation results indicate that the maximum velocity and acceleration time of the power mode are better than those in the economy mode. Fuel consumption of the economy mode is better than that in the power mode. Fuel consumption of PHEV during the CS period is further improved by using the methods proposed in this paper, and this is meaningful for research and development of PHEV.

Analysis of Hybrid Rechargeable Energy Storage Systems in Series Plug-In Hybrid Electric Vehicles Based on Simulations

In this paper, an extended analysis of the performance of different hybrid Rechargeable Energy Storage Systems (RESS) for use in Plug-in Hybrid Electric Vehicle (PHEV) with a series drivetrain topology is analyzed, based on simulations with three different driving cycles. The investigated hybrid energy storage topologies are an energy optimized lithium-ion battery (HE) in combination with an Electrical Double-Layer Capacitor (EDLC) system, in combination with a power optimized lithium-ion battery (HP) system or in combination with a Lithium-ion Capacitor (LiCap) system, that act as a Peak Power System. From the simulation results it was observed that hybridization of the HE lithium-ion based energy storage system resulted from the three topologies in an increased overall energy efficiency of the RESS, in an extended all electric range of the PHEV and in a reduced average current through the HE battery. The lowest consumption during the three driving cycles was obtained for the HE-LiCap topology, where fuel savings of respectively 6.0%, 10.3% and 6.8% compared with the battery stand-alone system were achieved. The largest extension of the range was achieved for the HE-HP configuration (17% based on FTP-75 driving cycle). HP batteries however have a large internal resistance in comparison to EDLC and LiCap systems, which resulted in a reduced overall energy efficiency of the hybrid RESS. Additionally, it was observed that the HP and LiCap systems both offer significant benefits for the integration of a peak power system in the drivetrain of a Plug-in Hybrid Electric Vehicle due to their low volume and weight in comparison to that of the EDLC system.

Study on load performance of electric motor system used in hybrid electric vehicle

The performance of the power assist, global optimization solved by dynamic programming （DP） method, Chery and Insight control strategies are analyzed using the mild parallel hybrid electric vehicle （PHEV） model based on Insight structure. The influence of the four control strategies to the load power of the electric motor system used on parallel hybrid electric vehicle is studied. It is found that 80 percent of the motor load power points are under 1/5 of the electric peak power. The motor load power of the power assist control strategy is distributed in the widest range during generating operation, and the motor load power of the global optimization control strategy has the smallest one.

Study on ultracapacitor-battery hybrid power system for PHEV applications

For the battery only power system is hard to meet the energy and power requirements reasonably, a hybrid power system with uhracapacitor and battery is studied. A Topology structure is analyzed that the uhracapacitor system is connected with battery pack parallel after a bidirectional DC/DC converter. The ultracapacitor, battery and the hybrid power system are modeled. For the plug-in hybrid electric vehicle （PHEV） application, the control target and control strategy of the hybrid power system are put forward. From the simulation results based on the Chinese urban driving cycle, the hybrid power system could meet the peak power requirements reasonably while the battery pack＇ s current is controlled in a reasonable limit which will be helpful to optimize the battery pack＇ s working conditions to get long cycling life and high efficiency.

Applications of Serial-Parallel Compensated Resonant Topology in Wireless Charger System Used in Electric Vehicles

There are lots of factors that can influence the wireless charging efficiency in practice, such as misalignment and air-gap difference, which can also change all the charging parameters. To figure out the relationship between those facts and system, this paper presents a serial-parallel compensated(SPC) topology for electric vehicle/plug-in hybrid electric vehicle(EV/PHEV) wireless charger and provides all the parameters changing with corresponding curves. An ANSYS model is built to extract the coupling coefficient of coils. When the system is works at constant output power, the scan frequency process can be applied to wireless power transfer(WPT) and get the resonant frequency. In this way, it could determine the best frequency for system to achieve zero voltage switching status and force the system to hit the maximum transmission efficiency. Then frequency tracking control(FTC) is used to obtain the highest system efficiency. In the paper, the designed system is rated at 500 W with 15 cm air-gap, the overall efficiency is 92%. At the end, the paper also gives the consideration on how to improve the system efficiency.

Performance Analysis of Plug-in Hybrid Passenger Vehicles

PHEVs （passenger plug-in hybrid electric vehicles） have shown significant fuel reduction potential. Furthermore, PHEVs can also improve longitudinal vehicle dynamics with respect to acceleration and engine elasticity. The objective of this study is to investigate potential of concurrent optimization of fuel efficiency and driving performance. For the studies, a backward vehicle model for a parallel PHEV was designed, where the power flow is calculated from the wheels to the propulsion units, the conventional ICE （internal combustion engine） and the EMG （electric motor/generator） unit. The hybrid drive train is according to a P2 layout, consequently the EMG is situated between the shifting clutch and the ICE. The implemented operation strategy distributes the power to both propulsion units depending on the vehicle speed, requested driving torque, the battery＇s SOC （state of charge） and SOP （state of power）. Additional information, such as the slope of the road, can be taken into account by the operation strategy. In the paper, the fuel saving potential as well as the longitudinal dynamics change of different PHEV configurations is presented as a function of battery capacity and EMG power. Consequently, applicable hybrid components can be defined. By using additional information of the environment like various sensor data, road slope amongst others, the fuel saving potential can be improved even more. By studying the dynamic model, the overall results of the backward model are confirmed. In conclusion, this study shows that it is possible to concurrently reduce fuel consumption and increase driving performance in PHEVs. The potential depends strongly on the configuration of the electric components and the implemented operation strategy. Consequently, the hybrid system configuration has to be chosen carefully and aligned to the vehicle performance.

Analysis and Optimization of Transient Mode Switching Behavior for Power Split Hybrid Electric Vehicle with Clutch Collaboration

The power split hybrid electric vehicle(HEV)adopts a power coupling configuration featuring dual planetary gearsets and multiple clutches,enabling diverse operational modes through clutch engagement and disengagement.The multi-clutch configuration usually involves the collaboration of two clutches during the transient mode switching process,thereby substantially elevating control complexity.This study focuses on power split HEVs that integrate multi-clutch mechanisms and investigates how different clutch collaboration manners impact the characteristics of transient mode switching.The powertrain model for the power-split HEV is established utilizing matrix-based methodologies.Through the formulation of clutch torque curves and clutch collaboration models,this research systematically explores the effects of clutch engagement timing and the duration of clutch slipping state on transient mode switching behaviors.Building upon this analysis,an optimization problem for control parameters pertaining to the two collaborative clutches is formulated.The simulated annealing algorithm is employed to optimize these control parameters.Simulation results demonstrate that the clutch collaboration manners have a great influence on the transient mode switching performance.Compared with the pre-calibrated benchmark and the optimal solution derived by the genetic algorithm,the maximal longitudinal jerk and clutch slipping work during the transient mode switching process is reduced obviously with the optimal control parameters derived by the simulated annealing algorithm.The study provides valuable insights for the dynamic coordinated control of the power-split HEVs featuring complex clutch collaboration mechanisms.

SOC estimation of lithium-ion power battery for HEV based on advanced wavelet neural network

In order to improve the estimation accuracy of the battery＇s state of charge（SOC） for the hybrid electric vehicle（HEV）,the SOC estimation algorithm based on advanced wavelet neural network（WNN） is presented.Based on advanced WNN,the SOC estimation model of a lithium-ion power battery for the HEV is first established.Then,the convergence of the advanced WNN algorithm is proved by mathematical deduction.Finally,using an adequate data sample of various charging and discharging of HEV batteries,the neural network is trained.The simulation results indicate that the proposed algorithm can effectively decrease the estimation errors of the lithium-ion power battery SOC from the range of ±8% to ±1.5%,compared with the traditional SOC estimation methods.

Machine learning modeling for fuel cell-battery hybrid power system dynamics in a Toyota Mirai 2 vehicle under various drive cycles

Electrification is considered essential for the decarbonization of mobility sector, and understanding and modeling the complex behavior of modern fuel cell-battery electric-electric hybrid power systems is challenging, especially for product development and diagnostics requiring quick turnaround and fast computation. In this study, a novel modeling approach is developed, utilizing supervised machine learning algorithms, to replicate the dynamic characteristics of the fuel cell-battery hybrid power system in a 2021 Toyota Mirai 2nd generation (Mirai 2) vehicle under various drive cycles. The entire data for this study is collected by instrumenting the Mirai vehicle with in-house data acquisition devices and tapping into the Mirai controller area network bus during chassis dynamometer tests. A multi-input - multi-output, feed-forward artificial neural network architecture is designed to predict not only the fuel cell attributes, such as average minimum cell voltage, coolant and cathode air outlet temperatures, but also the battery hybrid system attributes, including lithium-ion battery pack voltage and temperature with the help of 15 system operating parameters. Over 21,0000 data points on various drive cycles having combinations of transient and near steady-state driving conditions are collected, out of which around 15,000 points are used for training the network and 6,000 for the evaluation of the model performance. Various data filtration techniques and neural network calibration processes are explored to condition the data and understand the impact on model performance. The calibrated neural network accurately predicts the hybrid power system dynamics with an R-squared value greater than 0.98, demonstrating the potential of machine learning algorithms for system development and diagnostics.

Modeling and optimal energy management of a power split hybrid electric vehicle

With the combination of engine and two electric machines, the power split device allows higher efficiency of the engine. The operation modes of a power split HEV are analyzed, and the system dynamic model is established for HEV forward simulation and controller design. Considering the fact that the operation modes of the HEV are event-driven and the system dynamics is continuous time-driven for each mode, the structure of the controller is built and described with the hybrid automaton control theory. In this control structure, the mode selection process is depicted by the finite state machine （FSM）. The multi-mode switch controller is designed to realize power distribution. Furthermore, the vehicle mode operations are optimized, and the nonlinear model predictive control （NMPC） strategy is applied by implementing dynamic programming （DP） in the finite pre- diction horizon. Comparative simulation results demonstrate that the hybrid control structure is effective and feasible for HEV energy management design. The NMPC optimal strategy is superior in improving fuel economy.

Powertrain control of a solar photovoltaic-battery powered hybrid electric vehicle

This paper proposes a powertrain controller for a solar photovoltaic battery powered hybrid electric vehicle (HEV). The main objective of the proposed controller is to ensure better battery management, load regulation, and maximum power extraction whenever possible from the photovoltaic panels. The powertrain controller consists of two levels of controllers named lower level controllers and a high-level control algorithm. The lower level controllers are designed to perform individual tasks such as maximum power point tracking, battery charging, and load regulation. The perturb and observe based maximum power point tracking algorithm is used for extracting maximum power from solar photovoltaic panels while the battery charging controller is designed using a PI controller. A high-level control algorithm is then designed to switch between the lower level controllers based on different operating conditions such as high state of charge, low state of charge, maximum battery current, and heavy load by respecting the constraints formulated. The developed algorithm is evaluated using theoretical simula-tion and experimental studies. The simulation and experimental results are presented to validate the proposed technique.

含新能源和电动汽车充电站并网的主动配电网无功优化模型

针对新能源和电动汽车充电站规模化并网引起的无功优化问题,首先建立以主动配电网运行成本和电压偏差最小,系统稳定性最优的多目标无功优化模型。其次,基于PV曲线上、下半支解的接近程度,提出一种新的静态电压稳定性指标,以改善系统电压稳定性。最后,采用具有交叉反馈机制的混合优化算法对模型进行求解,并提出一种基于Tent混沌映射和自适应变异算子的改进飞蛾扑火算法提高求解效率。仿真结果表明,所提模型在降低系统运行成本,减少电压波动的同时,还能提高系统稳定性,且该混合优化算法能够快速、准确地求解混合整数的非凸、非线性优化模型。

含分布式电源和电动汽车的配电网可靠性评估

针对目前大规模分布式电源和电动汽车接入配电网后,给配电网可靠性带来一定影响的问题,提出了一种含有分布式电源和电动汽车的新型配电网的可靠性评估方法。首先,考虑到风光出力的不确定性和相关性,选择拟合性最优的Frank-Copula函数,建立了风光联合出力概率模型。其次,分析了电动汽车用户行为特征,提出了基于动态分时电价的电动汽车有序充放电控制策略。最后,基于改进IEEE-RBTS Bus6测试系统的主馈线F4,对系统的可靠性指标进行计算分析,结果表明所提的风光联合出力模型和有序充放电控制策略可以有效降低对配电网可靠性的影响。

混合动力汽车无法READY的故障诊断

随着环保意识的增强和能源危机的加剧,新能源电动汽车技术迅速发展,已成为当前汽车工业的重点研究方向。作为新能源汽车类型之一的混合动力汽车,其结构组成既有传统汽车结构又有电动汽车结构,加上电子控制系统复杂,其故障诊断对专业技术人员的要求非常高。首先阐述混合动力汽车动力系统的基本组成和工作原理,并分析混合动力汽车电池系统的组成和控制原理,以普锐斯混合动力汽车无法READY (准备就绪)故障为例,基于故障诊断基本策略方法,借助故障诊断设备进行故障原因分析和诊断,为同行提供一种混动汽车的故障诊断思路,具有一定的参考价值。

考虑车网互动的园区电网动态双层能量管理策略

为解决大量接入的清洁能源出力波动和充电场内汽车数量的随机变化给电网能量管理带来的困难,提出一种园区电网双层优化控制策略.上层基于模型预测控制技术建立风光储集成动态优化模型,综合应用园区电池储能系统和电动汽车(EV)电池储能系统参与电网能量平衡.下层则考虑同时满足EV车主对EV的充电需求和上层能量调度的车网互动管理需求,制定园区电网内停车场的EV有序充放电策略.仿真算例验证表明:所提策略能将分散园区各处的EV储能集成为统一虚拟储能,扩展园区电网储能系统,增加可再生分布式电源的消纳与园区电网的经济效益.

混合动力汽车驱动策略与能量回收的发展综述

混合动力汽车可以通过协调不同的动力来源和回收制动能量来满足电力需求,从而优化能源使用效率和汽车行驶性能。首先对串联式、并联式和混联式这三种混合动力汽车动力系统结构进行了深入分析,接着讨论了能量管理策略,最后研究了制动能量回收和能量计算,以及制动回收能量结构与流程和影响能量回收的因素。希望为后续从事相关工作的研究者做出参考贡献。

混合动力汽车功率分流传动系统扭转振动及其影响因素研究

针对某款混合动力汽车,综合考虑发动机、电机、复合行星齿轮机构、离合器、减速器、差速器和半轴等部件,采用集中质量法建立功率分流传动系统动力学模型。在此基础上,分析不同运行工况下传动系统固有频率和振型,分别研究电机和发动机激振频率与传动系统固有频率之间的关系,仿真分析扭转减振器刚度对传动系统固有频率的影响规律,通过改变扭转减振器刚度从而使得传动系统共振转速远离发动机常用工作区。