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.

Realization and Analysis of Good Fuel Economy and Kinetic Performance of a Low-cost Hybrid Electric Vehicle

By using high-power and high-efficiency propulsion systems,current hybrid electric vehicles（HEVs） in market can achieve excellent fuel economy and kinetic performance.However,it is the cost of current HEVs that hinders HEVs coming into widespread use.A novel hybrid electric propulsion system is designed to balance HEV cost and performance for developing markets.A battery/supercapacitor-based hybrid energy storage system（HESS） is used to improve energy conversion efficiency and reduce battery size and cost.An all-in-one-controller（AIOC） which integrates engine electronic control unit（ECU）,motor ECU,and HESS management system is developed to save materials and energy,and reduce the influence of distribution parameters on circuit.As for the powertrain configuration,four schemes are presented：belt-driven starter generator（BSG） scheme,four-wheel drive HEV scheme,full HEV scheme,and ranger-extender electric vehicle（EV） scheme.Component selection and parameter matching for the propulsion system are performed,and an energy management strategy is developed based on powertrain configuration and selected components.Forward-facing simulation models are built,comprehending the control strategy based on the optimal engine torque for the low-cost hybrid electric propulsion system.Co-simulation of AVL CRUISE and Matlab/Simulink is presented and the best scheme is selected.The simulation results indicate that,for the best design,fuel consumption in urban driving condition is 4.11 L/（100 km） and 0-50 km/h accelerating time is 10.95 s.The proposed research can realize low-cost concept for HEV while achieving satisfactory fuel economy and kinetic performance,and help to improve commercialization of HEVs.

Multi-objective comprehensive optimization of fuel consumption and emission for hybrid electric vehicles

Aiming to reduce fuel consumption and emissions of a dual-clutch hybrid electric vehicle during cold start, multiobjective optimization for fuel consumption and HC/CO emission from a TWC(three-way catalytic converter) outlet is presented in this paper. DP(dynamic programming) considering dual-state variables is proposed based on the Bellman optimality principle. Both the battery SOC(state of charge) and the temperature of TWC monolith are considered in the algorithm simultaneously. In this way the global optimal control strategy and the Pareto optimal solution of multi-objective function are derived. Simulation results show that the proposed method is able to promote the TWC light-off significantly by decreasing the engine's load and improving exhaust temperature from the outlet of the engine, in comparison with original DP considering the single battery SOC. Compared to the results achieved by rule-based control strategy, fuel economy and emission of TWC outlet for cold start are optimized comprehensively. Each indicator of Pareto solution set shows the significant improvement.

A comparative study of hybrid electric vehicle fuel consumption over diverse driving cycles

Environmental pollution and declining resources of fossil fuels in recent years,have increased demand for better fuel economy and less pollution for ground transportation.Among the alternative solutions provided by researchers in recent decades,hybrid electric vehicles consisted of an internal combustion engine and an electric motor have been considered as a promising solution in the short-term.In the present study,fuel economy characteristics of a parallel hybrid electric vehicle are investigated by using numerical simulation.The simulation methodology is based on a fast forward facing simulation model of a parallel hybrid and an internal combustion engine powertrains.The objective of this study is to present the main parameters which result in an optimum combination of hybrid powertrain components in order to obtain a better fuel economy of hybrid powertrains regarding different driven cycles and hybridization factors.Then,the fuel consumption of the parallel hybrid electric vehicles are compared considering various driven cycles and hybridization factors.The results showed that the better fuel economy of hybrid powertrains increases by decreasing average load of the test cycle and the point of the best fuel economy for a particular average load of the cycle moves towards higher hybridization factors when the average load of the test cycle is reduced.

A Novel Method for the Application of the ECMS(Equivalent Consumption Minimization Strategy)to Reduce Hydrogen Consumption in Fuel Cell Hybrid Electric Vehicles

Fuel cell hybrid electric vehicles are currently being considered as ideal means to solve the energy crisis and global warming in today’s society.In this context,this paper proposes a method to solve the problem related to the dependence of the so-called optimal equivalent factor(determined in the framework of the equivalent consumption minimum strategy-ECMS)on the working conditions.The simulation results show that under typical conditions(some representative cities being considered),the proposed strategy can maintain the power balance;for different initial battery’s states of charge(SOC),after the SOC stabilizes,the fuel consumption is 5.25 L/100 km.

MODELING AND IMPLEMENTATION OF SPEED GOVERNOR FOR THE HYBRID ELECTRIC VEHICLE ENGINE

A speed control analysis for an in-line gasoline fueled internal combustion （IC） engine is presented for the purpose of alleviation of high frequency oscillations in engine revolutions. A dynamic cylinder-by-cylinder model is proposed, base on slider-crank mechanism, which is extended to develop a digital governor providing a high fidelity estimation of rotary speed oscillation for hybrid vehicle engines. A modified PID controller that P and I gain is placed in feedback path is also described for hybrid electric vehicle （HEV） engine speed regulation, By comparison between measured and estimated signals, it is demonstrated that a good agreement has been achieved and the governor behaves an excellent damping speed ripple.

An optimal energy management development for various configuration of plug-in and hybrid electric vehicle

Due to soaring fuel prices and environmental concerns, hybrid electric vehicle(HEV) technology attracts more attentions in last decade. Energy management system, configuration of HEV and traffic conditions are the main factors which affect HEV's fuel consumption, emission and performance. Therefore, optimal management of the energy components is a key element for the success of a HEV. An optimal energy management system is developed for HEV based on genetic algorithm. Then, different powertrain system component combinations effects are investigated in various driving cycles. HEV simulation results are compared for default rule-based, fuzzy and GA-fuzzy controllers by using ADVISOR. The results indicate the effectiveness of proposed optimal controller over real world driving cycles. Also, an optimal powertrain configuration to improve fuel consumption and emission efficiency is proposed for each driving condition. Finally, the effects of batteries in initial state of charge and hybridization factor are investigated on HEV performance to evaluate fuel consumption and emissions. Fuel consumption average reduction of about 14% is obtained for optimal configuration data in contrast to default configuration. Also results indicate that proposed controller has reduced emission of about 10% in various traffic conditions.

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.

Design and Analysis of Electro-mechanical Hybrid Anti-lock Braking System for Hybrid Electric Vehicle Utilizing Motor Regenerative Braking

Braking on low adhesion-coefficient roads, hybrid electric vehicle＇s motor regenerative torque is switched off to safeguard the normal anti-lock braking system （ABS） fimction. When the ABS control is terminated, the motor regenerative braking is readmitted. Aiming at avoiding permanent cycles from hydraulic anti-lock braking to motor regenerative braking, a novel electro-mechanical hybrid anti-lock braking system using fuzzy logic is designed. Different from the traditional single control structure, this system has a two-layered hierarchical structure, The first layer is responsible for harmonious adjustment or interaction between regenerative system and anti-lock braking system. The second layer is responsible for braking torque distribution and adjustment. The closed-loop simulation model is built. Control strategy and method for coordination between regenerative and anti-lock braking are developed. Simulation braking on low adhesion-coefficient roads with fuzzy logic control and real vehicle braking field test are presented. The results from simulating analysis and experiment show braking performance of the vehicle is perfect, harmonious coordination between regenerative and anti-lock braking function, significant amount of braking energy can be recovered and the proposed control strategy and method are effective.

Quantitative Comparison of Partitioned-Stator Machines for Hybrid Electric Vehicles

In this paper,three partitioned-stator(PS)machines,namely the PS flux-switching DC-field(PS-FSDC)machine,the PS-FS hybrid-excitation(PS-FSHE)machine,and the flux adjuster FS permanent-magnet(FA-FSPM)machine are proposed.With different flux-regulating mechanisms,all three proposed machines can offer satisfactory flux-weakening capabilities for wide-speed range operations.Unlike the traditional PS machine that installs the armature windings and the excitation sources in the outer-stator and inner-stator,respectively;the proposed machines purposely swap the installation arrangements.Upon the proposed structure,the FA-FSPM machine can fully utilize the stator core for PM material accommodations.As a result,excellent power and torque densities can be achieved.To verify the proposed concepts,these three PS machines are quantitatively compared based on the hybrid electric vehicle(HEV)specifications.

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.

A multivariable output neural network approach for simulation of plug-in hybrid electric vehicle fuel consumption

This study is laser focused on the simulation of fuel consumption and fuel economy label parameters of plug-in hybrid electric vehicles.While fuel economy is a key factor in the design of plug-in hybrid electric vehicles,a fuel economy label can educate customers about the economic advantage of purchasing a particular car.The fuel economy label of a PHEV consists of parameters like driving range,electrical energy consumption,fuel economy for city,highway,and combined use,battery recharge time,and fuel consumption rates.The study used an inverse function model of an artificial neural network to simulate and calculate the parameters of the fuel economy labels of PHEVs.Firstly,the selected parameters of the fuel economy label of plug-in hybrid electric vehicles were used to develop a single output model.The output variable of the single output model was then merged with dummy functions to form input variables for the inverse function model.The output variables simulated were engine size in litres;estimated driving range when the battery is fully charged in km,battery recharged time in hours,city fuel consumption(L/100 km),highway fuel consumption(L/100 km),combined fuel consumption(L/100 km),estimated driving range when the tank is full,carbon dioxide(CO_(2))emission in grams/km,electric motor power in kW,number of cylinders,and electrical charges consumed in kWh/100 km.Different cases of input variables were considered for the inverse function model.The accuracy of the model was 29.1 times greater than that of the conventional inverse artificial neural network model.

Function approximation reinforcement learning of energy management with the fuzzy REINFORCE for fuel cell hybrid electric vehicles

In the paper,a novel self-learning energy management strategy(EMS)is proposed for fuel cell hybrid electric vehicles(FCHEV)to achieve the hydrogen saving and maintain the battery operation.In the EMS,it is proposed to approximate the EMS policy function with fuzzy inference system(FIS)and learn the policy parameters through policy gradient reinforcement learning(PGRL).Thus,a so-called Fuzzy REINFORCE algorithm is first proposed and studied for EMS problem in the paper.Fuzzy REINFORCE is a model-free method that the EMS agent can learn itself through interactions with environment,which makes it independent of model accuracy,prior knowledge,and expert experience.Meanwhile,to stabilize the training process,a fuzzy baseline function is adopted to approximate the value function based on FIS without affecting the policy gradient direction.More-over,the drawbacks of traditional reinforcement learning such as high computation burden,long convergence time,can also be overcome.The effectiveness of the proposed methods were verified by Hardware-in-Loop ex-periments.The adaptability of the proposed method to the changes of driving conditions and system states is also verified.

An investigation of cam-roller mechanism applied in sphere cam engine

As an alternative power source for hybrid electrical vehicle(HEV), electric generating system(EGS) driven by sphere cam engine(SCE) is said to own higher power density and integration. In this work, the structure and working principle of EGS were introduced, based on which the advantages of EGS were displayed. The profile of sphere cam was achieved after the desired motion of piston was given. After establishing the dynamic model of power transmission mechanism, the characteristics of cam-roller mechanism were studied. The results show that the optimal cam profile of SCE is a sinusoid curve which has two peaks and two valleys and a mean pressure angle of 47.19°. Because of the special cam shape, the trace of end surface center of piston is an eight-shape curve on a specific sphere surface. SCE running at speed of 3000 r/min can generate the power of 33.81 kW, which could satisfy the need of HEVs. However, the force between cylinder and piston skirt caused by Coriolis acceleration can reach up to 1182 N, which leads to serious wear between cylinder liner and piston skirt and may shorten the lifespan of SCE.

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.

Energy Management Strategy for Hybrid Electric Vehicle Based on System Efficiency and Battery Life Optimization

A novel method to calculate fuel-electric conversion factor for full hybrid electric vehicle（HEV）equipped with continuously variable transmission（CVT）is proposed.Based on consideration of the efficiency of pivotal components,electric motor,system efficiency optimization models are developed.According to the target of instantaneous optimization of system efficiency,operating ranges of each mode of power-train are determined,and the corresponding energy management strategies are established.The simulation results demonstrate that the energy management strategy proposed can substantially improve the vehicle fuel economy,and keep battery state of charge（SOC）change in a reasonable variation range.

Optimal Energy Management for a Complex Hybrid Electric Vehicle:Tolerating Power-loss of Motor

The energy management may perform well under normal conditions, but may lead to poor behavior under abnormal situations. To tackle this problem, an optimal control strategy called rule-based equivalent fuel consumption minimization strategy (RECMS) is developed for a new complex hybrid electric vehicle (CHEV). It optimizes the energy effciency and drive performance to cater for normal and power-loss operations of the tractive motor. Firstly, the strategy formulates a novel objective function based on the equivalent fuel concept. By accounting for the actual fuel cost, the equivalent fuel cost for the electric machines and virtual fuel cost for the drivability, the cost function is obtained. Furthermore, some penalty factors are presented to optimize the performance target. Finally, experiments for a practical CHEV are performed to validate a simulation model. Then simulations are carried out for both rule-based and RECMS. The results show that the optimal energy management is working well.

Closed-form solution to the dynamic programming for a heavy-duty parallel hybrid vehicle energy management

Dynamic programming(DP)is frequently used to obtain the optimal solution to the hybrid electric vehicle(HEV)energy management.The trade-off between the accuracy and the computational effort is the biggest problem for the DP method.The closed-form solution to the DP is proposed to solve this problem.Firstly,the affine linear model of the engine fuel rate is obtained based on engine test data.The piecewise linear approximation of the motor power demand is obtained considering the different energy flows in the charging and discharging stages of the battery.Then,the second-order Taylor expansion for the cost matrix at each time and state grid point is introduced to get the closed-form solution of the optimal torque split.The results show that this method can greatly reduce the computing burden by 93%while ensuring near-optimal fuel economy compared with the conventional DP method.

基于充电行为电量规划的自适应能量管理策略

为提高插电式混合动力汽车(PHEV)的燃油经济性,以并联式PHEV为研究对象,考虑驾驶员充电行为,提出基于充电行为电量规划和等效燃油消耗最小策略(ECMS)的自适应能量管理策略。构建了包含不同类型工况的组合工况。根据驾驶员的充电行为特征(充电频率、充电上限、放电下限)进行充电行为分析,并进行4类工况电量消耗与燃油消耗ECMS策略下的离线仿真数据获取。根据驾驶员充电行为以及离线数据进行SOC轨迹的规划。结果表明:在电池SOC初始值分别为0.9、0.6时,提出的能量管理策略相较于基于电量消耗维持的等效燃油消耗策略,整车燃油经济性分别提升7.87%和13.1%。

燃油车和纯电车混杂智能网联队列系统的节能与稳定控制

提出了一种燃油汽车和纯电动汽车混杂的异构智能网联队列系统节能策略与稳定控制方法。考虑了异质车辆动力学特征、通讯时滞和外界干扰等多重不利因素对队列稳定性的影响,建立了异质车辆队列非线性系统动力学模型和能耗模型;基于能耗成本和后退动态规划方法,推导出了单车经济车速;依据所提出的节能型车间距策略,构建了状态跟踪误差系统;基于连续时间域分布式鲁棒控制方法,给出了在干扰和信息时滞下的队列系统稳定判据。对包含4辆跟随车的混杂队列系统进行仿真测试。结果表明:在保持队列系统稳定的前提下,4辆跟随车辆节能效果分别提高1.90%、1.25%、19.11%和12.22%。