Implementation of Fuzzy Logic Control into an Equivalent Minimization Strategy for Adaptive Energy Management of A Parallel Hybrid Electric Vehicle

As government agencies continue to tighten emissions regulations due to the continued increase in greenhouse gas production, automotive industries are seeking to produce increasingly efficient vehicle technology. Hybrid electric vehicles (HEVs) have been introduced to mitigate problems while improving fuel economy. HEVs have led to the demand of creating more advanced controls software to consider multiple components for propulsive power in a vehicle. A large section in the software development process is the implementation of an optimal energy management strategy meant to improve the overall fuel efficiency of the vehicle. Optimal strategies can be implemented when driving conditions are known a prior. The Equivalent Consumption Minimization Strategy (ECMS) is an optimal control strategy that uses an equivalence factor to equate electrical to mechanical power when performing torque split determination between the internal combustion engine and electric motor for propulsive and regenerative torque. This equivalence factor is determined from offline vehicle simulations using a sensitivity analysis to provide optimal fuel economy results while maintaining predetermined high voltage battery state of charge (SOC) constraints. When the control hierarchy is modified or different driving styles are applied, the analysis must be redone to update the equivalence factor. The goal of this work is to implement a fuzzy logic controller that dynamically updates the equivalence factor to improve fuel economy, maintain a strict charge sustaining window of operation for the high voltage battery, and reduce computational time required during algorithm development. The adaptive algorithm is validated against global optimum fuel economy and charge sustaining results from a sensitivity analysis performed for multiple drive cycles. Results show a maximum fuel economy improvement of 9.82% when using a mild driving style and a 95% success rate when maintaining an ending SOC within 5% of the desired SOC regardless of starting SOC.

Hybrid Energy Systems and the Logic of Their Service-Dominant Implementation: Screening the Pathway to Improve Results

The transition of the global economy to a low-carbon development path has led to dramatic changes in the organization and functioning of energy markets around the world,where hybrid energy systems(HESs)are one of the decisive active agents.At the same time,a number of problems facing the modern HESs are primarily due to the stochastic nature of the renewable energy they use,require further profound changes not only in the technologies they use and how they manage them,necessary to meet the needs of end consumers and interact with the unified energy system,but also to preserve the ability of the environment to self-heal.In order to make the process of changes more efficient and eco-deep,the article proposes to use and discusses the approach based on service dominant(SD)logic,which opens up new opportunities for solving the problems of HESs.First of all through:the implementation of closer service interaction with other participants in the energy markets,as well as with the environment;a systemically organized process of transforming the“product”economic activity of HESs into a service-dominant one;developing the generalized and engineering models for solving the problems of optimizing the technical and economic indicators of HESs,operation in steady-state and transient modes.The calculations confirm the effectiveness of the proposed approach and its ability to reduce the average daily costs for the system as a whole by 14.7%compared to the costs with a uniform distribution of power between the modules.

Controlling Torque Distribution for Parallel Hybrid Vehicle Based on Hierarchical Structure Fuzzy Logic

The Hierarchical Structure Fuzzy Logic Control (HSFLC) strategies of torque distribute for Parallel Hybrid Electric Vehicle (PHEV) in the mode of operation of the vehicle i. e. , acceleration, cruise, deceleration etc. have been studied. Using secondly developed the hybrid vehicle simulation tool ADVISOR, the dynamic model of PHEV has been set up by MATLAB/SIMULINK. The engine, motor as well as the battery characteristics have been studied. Simulation results show that the proposed hierarchical structured fuzzy logic control strategy is effective over the entire operating range of the vehicle in terms of fuel economy. Based on the analyses of the simulation results and driver’s experiences, a fuzzy controller is designed and developed to control the torque distribution. The controller is evaluated via hardware-in-the-loop simulator (HILS). The results show that controller verify its value.

Control strategy for hybrid tracked vehicles using fuzzy logic

To solve the problem of power distribution for hybrid tracked vehicles （HTV）, a supervi- sory control strategy is proposed. Firstly, power system integration is analyzed and modeled. Then the control algorithm is given. Two fuzzy logics are used to realize the coordination control over each power unit. One controls power distribution based on the load power and battery state of charge （SOC）. The other manage the power during regenerating braking. To validate the presented control strategy, a ＂driver and controller＂ in the loop simulation platform is built based on dSPACE system and real-time simulation is made. The simulation results show that the strategy presented can solve the power distribution problem of hybrid tracked vehicles correctly and effectively.

Hybrid Genetic Algorithms with Fuzzy Logic Controller

In this paper, a new implementation of genetic algorithms (GAs) is developed for the machine scheduling problem, which is abundant among the modern manufacturing systems. The performance measure of early and tardy completion of jobs is very natural as one's aim, which is usually to minimize simultaneously both earliness and tardiness of all jobs. As the problem is NP-hard and no effective algorithms exist, we propose a hybrid genetic algorithms approach to deal with it. We adjust the crossover and mutation probabilities by fuzzy logic controller whereas the hybrid genetic algorithm does not require preliminary experiments to determine probabilities for genetic operators. The experimental results show the effectiveness of the GAs method proposed in the paper.

Dehydration of Agro Products in a Hybrid Solar Dryer Controlled through a Fuzzy Logic System

Drying is one of the most energy-intensive processes in agro-products industry. For this reason, using solar energy appears as an attractive not polluting alternative to be used in drying processes. However, the daily and seasonal fluctuations in the radiation level require using energy accumulators with phase change materials (paraffin wax), to have a continuous drying processes. In hybrid solar dryers with energy accumulation system, a control system is essential to coordinate the control valves that allow the income of air that comes from the solar panel or from the energy accumulator. In this work, we implemented an advances multivariable control system that uses fuzzy logic in the hybrid solar dryer. The dryer includes an energy accumulator panel with paraffin wax as phase change material. The input variables were ambient temperature and solar radiation, both not controllable. The controlled variables were the opening level of the solar panel and accumulator energy valves. The control program consisted in an algorithm implemented with the “Fuzzy” toolbox in Matlab. Data were acquired with OPTO 22. The control system performed adequately when used to dehydrate mushroom slices and plums. Closing or opening the respective valves as a response to the variations of solar radiation and ambient air temperature allowed optimizing the use of solar energy.

MLD-MPC Approach for Three-Tank Hybrid Benchmark Problem

The present paper aims at validating a Model Predictive Control(MPC),based on the Mixed Logical Dynamical(MLD)model,for Hybrid Dynamic Systems(HDSs)that explicitly involve continuous dynamics and discrete events.The proposed benchmark system is a three-tank process,which is a typical case study of HDSs.The MLD-MPC controller is applied to the level control of the considered tank system.The study is initially focused on the MLD approach that allows consideration of the interacting continuous dynamics with discrete events and includes the operating constraints.This feature of MLD modeling is very advantageous when an MPC controller synthesis for the HDSs is designed.Once the MLD model of the system is well-posed,then the MPC law synthesis can be developed based on the Mixed Integer Programming(MIP)optimization problem.For solving this MIP problem,a Branch and Bound(B&B)algorithm is proposed to determine the optimal control inputs.Then,a comparative study is carried out to illustrate the effectiveness of the proposed hybrid controller for the HDSs compared to the standard MPC approach.Performances results show that the MLD-MPC approach outperforms the standardMPCone that doesn’t consider the hybrid aspect of the system.The paper also shows a behavioral test of the MLDMPC controller against disturbances deemed as liquid leaks from the system.The results are very satisfactory and show that the tracking error is minimal less than 0.1%in nominal conditions and less than 0.6%in the presence of disturbances.Such results confirm the success of the MLD-MPC approach for the control of the HDSs.

混合级联H桥逆变器的新型SHEPWM功率均衡控制策略

对于直流侧电压比为1∶1∶2的混合级联H桥逆变器,传统的指定谐波消除脉宽调制法(SHEPWM)存在各单元间输出功率不均衡问题,因此,提出一种双层功率均衡调制策略。首先,通过对消谐方程组中的基波幅值方程表达式进行等效拆分,使2个低压H桥单元的输出电压基波幅值之和与高压H桥单元的输出电压基波幅值相等,实现了高低压H桥单元间的功率均衡,即外层功率均衡。其次,利用逻辑运算的方法对低压单元的初始驱动信号进行逻辑重组,实现2个低压单元间的功率均衡,即内层功率均衡;然后使用改进的实数型遗传算法(IRCGA-2)求出消谐方程组的解,消除指定的谐波,得到高质量的输出电压。最后,通过仿真和实验证明了调制策略的正确性与有效性。

基于T-S模糊逻辑的混合储能孤岛直流微电网功率分配控制

在含混合储能的直流微电网中,传统阻容下垂控制无法解决由线路电阻和负荷功率波动导致的系统功率分配失衡问题。为此,提出一种基于Takagi-Sugeno(T-S)模糊逻辑的自适应阻容下垂控制方法以实现混合储能的分频分配。根据蓄电池和超级电容的物理特性,建立单个蓄电池支路输出电压、蓄电池组间输出功率差额和阻性下垂系数之间的T-S模糊逻辑关系,以及单个超级电容支路输出功率及其变化率、超级电容组间功率差额和容性下垂系数之间的T-S模糊逻辑关系,并由此构建基于T-S模糊逻辑的阻容下垂控制器。推导含混合储能的直流微电网中各部分的平均阻抗模型,并采用阻抗比分析法对微电网的小信号稳定性进行研究。MATLAB/Simulink仿真结果表明,基于T-S模糊逻辑的阻容下垂控制可保证在线路电阻和负荷功率波动情况下系统功率的合理分配。

本土制造企业高端化转型的战略决策逻辑研究

依托纵贯式单案例研究方法,以实现高端化转型的本土领先企业雅迪为例,在内外部双重压力下,搭建了传统制造企业转型突围背后的决策逻辑动态演化模型。研究发现:①在本土制造企业高端化转型过程中,因果逻辑和效果逻辑间呈现出“关系依赖式共存”“冲突式共存”与“互补式共存”3种微观共存模式;②外部环境不确定性是决策逻辑“何时”转换的“触发器”,内部资源位置则是其“如何”转换的“使能器”,内外部压力间的动态适配是混合逻辑动态属性的重要来源;③分离或整合双重压力间的矛盾与悖论,将引致混合逻辑间消极的冲突或积极的互补,而兼具积极面与消极面的双元性认知特征,将有助于传统制造企业在高质量发展背景下动态维持竞争优势。

不对称三单元十三电平逆变器拓扑及其调制策略

相比于对称型级联H桥多电平逆变器,混合级联H桥多电平逆变器可以使用较少H桥单元得到更高质量的输出电压,但传统混合级联多电平逆变器工作时单元间会出现电流倒灌的现象。针对上述问题,对电压比为1:3结构的Ⅲ型逆变器进行了改进,提出了一类电压比为3:2:1结构的不对称三单元十三电平逆变器。并针对该逆变器提出了一种融合阶梯波与脉宽调制波优点的混合调制策略,对该调制策略下所得的部分脉冲进行逻辑运算并分配,解决了传统Ⅲ型逆变器所存在的电流倒灌问题,提高了输出电压的电能质量。该混合调制策略下高中压单元工作在较低频率,低压单元工作在较高频率,以保证逆变器的输出电压质量。最后通过仿真和实验共同验证了所提逆变器拓扑结构以及该混合调制策略的正确性和可行性。

基于油电混动六旋翼无人机的模糊PID飞行控制策略研究

针对油电混动六旋翼无人机飞行因燃油消耗而产生变载荷,进而导致飞行姿态响应迟钝的现象,设计出结合能量管理的模糊PID(proportion integration differentiation,PID)飞行控制策略。首先,以最大需求功率为2.0 kW、质量为18 kg的油电混动六旋翼无人机为研究对象,建立MATLAB/Simulink模型;其次,利用模糊算法对变载荷的质量和转动惯量进行模糊化-隶属度函数-规则库-反模糊化处理,实时调整PID值,解决姿态响应迟钝的问题;最后,设计阶梯和巡航工况,观测无人机的姿态响应情况。结果表明:燃油消耗会在姿态变动时,对位置偏移产生不利影响;与普通PID相比,提出的飞行控制策略会实时修正不同载荷下的PID参数,当飞行状况改变时,位置峰值偏移量为6 m,稳定性能良好;同时,在偏移修正方面,模糊PID可在20 s内对偏移量进行修正,并且能持续保持现有姿态,表明模糊PID飞行控制策略具有优异的跟随性能。

混合级联H桥低压单元功率均衡策略

目的三单元直流侧电压比为1∶1∶2型的混合级联H桥逆变器,在采用传统调制策略下,虽能够输出较好的电能质量,但逆变器低压单元在全调制度下会存在输出功率不均衡的问题,基于此,提出一种新型调制策略。方法基于传统的混合频率调制策略,首先对低压单元第二层载波进行重构,并利用重构后的载波特性为低压单元提供逻辑信号;其次通过对两个低压单元的脉冲信号进行逻辑运算控制,以获得低压单元功率开关器件的实际驱动信号,实现对低压单元脉冲信号的重新分配;为减少逆变器高压模块的开关损耗,对高压单元采用阶梯波调制方法。结果仿真结果表明:新型混合调制策略可以解决逆变器在全调制度下低压单元输出功率不均衡的问题,并且通过实验验证了新型调制策略可使低压单元输出功率达到近似1∶1的效果;仿真分析表明:采用新型调制策略的逆变器总谐波畸变率(Total Harmonic Distortion,THD)值有所降低。结论新型调制策略能够减少载波数目,均衡开关损耗,并且在保留传统混合频率调制优势的基础上,降低逆变器的THD含量,提高逆变器的电能输出质量,同时在两个载波周期内解决了低压单元全调制下输出功率不均衡的问题。

燃料电池船舶复合供能系统控制策略设计与仿真

针对燃料电池船舶复合供能系统中的燃料电池功率波动问题和储能单元电池荷电状态(State of Charge, SOC)极端分化问题,依据系统拓扑结构,提出基于负载功率频率分解与模糊逻辑控制法相结合的复合供能系统控制策略设计。采用实例仿真验证该设计的优势。结果表明,该设计可有效保持燃料电池输出功率平滑,对储能单元SOC具有良好的均衡控制效果。

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.

A Hybrid Approach to Modeling and Control of Vehicle Height for Electronically Controlled Air Suspension

The control problems associated with vehicle height adjustment of electronically controlled air suspension （ECAS） still pose theoretical challenges for researchers, which manifest themselves in the publications on this subject over the last years. This paper deals with modeling and control of a vehicle height adjustment system for ECAS, which is an example of a hybrid dynamical system due to the coexistence and coupling of continuous variables and discrete events. A mixed logical dynamical （MLD） modeling approach is chosen for capturing enough details of the vehicle height adjustment process. The hybrid dynamic model is constructed on the basis of some assumptions and piecewise linear approximation for components nonlinearities. Then, the on-off statuses of solenoid valves and the piecewise approximation process are described by propositional logic, and the hybrid system is transformed into the set of linear mixed-integer equalities and inequalities, denoted as MLD model, automatically by HYSDEL. Using this model, a hybrid model predictive controller （HMPC） is tuned based on online mixed-integer quadratic optimization （MIQP）. Two different scenarios are considered in the simulation, whose results verify the height adjustment effectiveness of the proposed approach. Explicit solutions of the controller are computed to control the vehicle height adjustment system in realtime using an offline multi-parametric programming technology （MPT）, thus convert the controller into an equivalent explicit piecewise affine form. Finally, bench experiments for vehicle height lifting, holding and lowering procedures are conducted, which demonstrate that the HMPC can adjust the vehicle height by controlling the on-off statuses of solenoid valves directly. This research proposes a new modeling and control method for vehicle height adjustment of ECAS, which leads to a closed-loop system with favorable dynamical properties.

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.

A Hybrid Model Predictive Control for Handling Infeasibility and Constraint Prioritization

A hybrid approach using MLD (mixed logical dynamical) framework to handle infeasibility and constraint prioritization issues in MPC (model predictive control) based on input-output model is introduced. By expressing constraint priorities as propositional logics and by transforming the propositional logics into inequalities,the infeasibility and constraint prioritization issues are solved in the MPC. Constraints with higher priorities are met first, and then these with lower priorities are satisfied as much as possible. This new approach is illustrated in the control of a heavy oil fractionator-Shell column. The overall control performance has been significantly improved through the infeasibility and control priorities handling.

An Investigation into Regenerative Braking Control Strategy for Hybrid Electric Vehicle

Energy regeneration during braking is an important technique for hybrid electric vehicle (HEV) to improve their fuel economy and extend their driving range. Due to the effect of regenerative braking torque which is added by electric motor, the braking torque distribution between front and rear axles should be changed and the control logic of anti-lock braking system (ABS) ought to be adjusted according to the regenerative braking torque. This paper put forward a braking control strategy for hybrid electric vehicle; the control strategy is implemented with eight DOFs (Degree-of-Freedom) nonlinear vehicle forward simulation model which is built under the environment of Matlab/Simulink. Based on target wheel slip ratio, a fuzzy logic approach was applied to maintain the optimal target slip ratio so that best compromise between hydraulic torque and regenerative torque can be obtained for the vehicle.

Modeling and Control of a Continuous Stirred Tank Reactor Based on a Mixed Logical Dynamical Model

A novel control strategy for a continuous stirred tank reactor(CSTR)system,which has the typical characteristic of strongly pronounced nonlinearity,multiple operating points,and a wide operating range,is initiated from the point of hybrid systems.The proposed scheme makes full use of the modeling power of mixed logical dy- namical(MLD)systems to describe the highly nonlinear dynamics and multiple operating points in a unified framework as a hybrid system,and takes advantage of the good control quality of model predictive control(MPC) to design a controller.Thus,this approach avoids oscillation during switching between sub-systems,helps to relieve shaking in transition,and augments the stability robustness of the whole system,and finally achieves optimal(i.e. fast and smooth)transition between operating points.The simulation results demonstrate that the presented ap- proach has a satisfactory performance.