This paper presents a novel concept, the Hybrid Power Pack (HPP), which consists of a hybridiza- tion kit for transforming small city cars, powered by an original diesel engine, into a parallel hy- brid vehicle. The study was jointly conducted by the University of Rome “Sapienza” and the Enea Casaccia research center. The idea is to design a hybridpowertrain that can be installed in a typi- cal microcar, which means that all systems and components will be influenced by the limited space available in the motor compartment of the vehicle. In this paper the details of the mechanical and electrical realization of the powertrain will be discussed and the simulation of a small city car equipped with HPP will be presented and the results discussed and analyzed. The hybrid system also includes the battery pack which is composed of twenty-four Li-ion cells made by EIG, con- nected in series. The storage system is controlled as regards the voltage and temperature by a Battery Management System (BMS). All the above components are connected and managed by a control unit. The HPP presented in this paper obtains a reduction in fuel consumption higher than 20%. The solution presented with the HPP with its management strategy and the addition of the “plug-in function” makes the hybridvehicle suitable in terms of performance and consumption in every driving conditions. The ideal strategy behind the “plug-in function” could represent a guide- line for further achievements and experimentations, because it offers a simple hardware layout and a real reduction in fuel consumption.
From those five types of commonly used battery, previous research stated that lithium-ion battery as the auxiliary power in FCHV can reduced fuel consumption to 2/3 of that without battery . It is one quantitative proof that lithium-ion battery is an excellent auxiliary power source to be hybridized with PEMFC. Somehow, the absence of a DC-DC converter connected to the fuel cell or the battery makes the system easier, lighter and cheaper previous analysis also stated that by adjusting the battery cell operating pressure, can result an active power sharing realized in a fuel cell/battery passive hybrid power source . This allows for sustaining the battery state of charge and to fulfill the power demand of an automotive powertrain.
Energy is one of the main requirements of human life and, in the last decade, the continuous development of technology has raised this need of energy . Furthermore, since the prices of petroleum products have been increasing, and due to advances in renewable energy technologies, it is widely acceptable today that renewables can play an important role in strengthening energy safekeeping. However, the availability of such a specific resource depends essentially on the specific changes in the weather variables; that is why hybrid renewable energy systems (HRES) are becoming a sufficiently promising energy generation application [2-3]. They are considered as a reasonable solution capable to cover the energy demand of residential, commercial, or institutional buildings. They can track load variations more closely, integrate a large range of technologies and avoid a centralized planning . Nonetheless, systems based on
This paper introduces a new control strategy “PWAM” method for HEV/EV motor drive system. This modulation method is quite different from other PWM methods that have been well researched or commonly used for the inverter in HEV/EV system. By using this method, only one phase leg of the inverter is doing switching action for every PWM-carrier period. The system configuration including green power generator, energy storage element, dc appliance and equipment, and energy management system with fuzzy logic will be introduced. The proposed integrated circuit allows the machine to operate in motor mode or acts as boost inductors of the boost converter, and thereby boosting the output torque coupled to the same transmission system or dc-link voltage of the inverter connected to the output of the integrated circuit. In motor mode, the proposed integrated circuit acts as an inverter and it becomes a boost-type boost converter, while using the motor windings as the boost inductors to boost the converter output voltage. Enhancement of a renewable power management system with intelligence control techniques (Fuzzy) for a micro grid system. Modeling, analysis, and control of distributed power sources and energy storage devices with MATLAB/ Simulink.
Renewable energy is currently widely used. One of these resources is solar energy. The photovoltaic (PV)array normallyuses a maximum power point tracking (MPPT) technique to continuously deliver the highest power to the load when thereare variations in irradiation and temperature. The disadvantage of PV energy is that the PV output power depends on weather conditions and cell temperature, making it an uncontrollable source. Furthermore, it is not available during the night. In order to overcome these inherent drawbacks, alternative sources, such as PEMFC, should be installed in the hybrid system. By changing the FC output power, the hybrid source output becomes controllable. However, PEMFC, in its turn, works only at a high efficiency within a specific power range , . The hybrid system can either be connected to the main grid or work autonomously with respect to the grid-connected mode or islanded mode, respectively. In the grid-connected mode, the hybrid source is connected to the main grid at the point of common coupling (PCC) to deliver power to the load. When load demand changes, the power supplied by the main grid and hybrid system must be properly changed. The power delivered from the main grid and PV array as well as PEMFC must be coordinated to meet load demand. Generally the hybrid source has two control modes: 1) unit-power control (UPC) mode and feeder-flow control (FFC) mode. In the UPC mode, variations of load demand are compensated by the main grid because the hybrid source output is regulated to reference power. Therefore, the reference value of the hybrid source output must be determined. In the FFC mode, the feeder flow is regulated to a constant, the extra load demand is picked up by the hybrid source, and hence, the feeder reference power must be known. Here Fuzzy logic or fuzzy set theory is a new method of controlling the MPPT is implemented in obtaining the peak power point. It has the advantage of being robust, fast in response. Fuzzy controller operates in two basic modes coarse and fine modes. The proposed fuzzy operating strategy is to coordinate the two control modes and determine the reference values of the fuzzy control so that all constraints are satisfied. This operating strategy will minimize the number of operating mode changes, improve performance of the system operation, and enhance system stability.
Afterwards, the rules of the EACS were described. A map of the optimal operation points of the ICE, in terms of FC and emissions, was achieved using the GC method, and is used in the EACS for de- termining the ICE operation point at each moment of the driving cycle. Since the parameters of the EACS impact its performance and, therefore, vehicle FC and emissions, these parameters were considered the remaining part of the optimization parameters. The aim of optimization was to attain an acceptable value for vehicle FC and emissions without sacricing dynamic performance. In order to optimize vehicle FC and emissions simultaneously, the GC method was employed. It can be concluded from the optimization results that the achieved values for the objectives are not the same utopia points, but are acceptable values. Then, it was demonstrated that the optimized parameters satisfy the PNGV criteria. Finally, the eectiveness of the simultaneous optimization was eval- uated by comparison with conventional methods and it was demonstrated that simultaneous optimization gives better results. Also, the optimized EACS and the DP strategy were compared using optimal transmission and the superiority of the EACS over the DP was shown.
ABSTRACT: This paper focuses on the study of hybridpowertrain circuit and important subsystems of a solar electric hybrid bus to reduce the manufacturing cost, operating cost and emissions. The powertrain circuit of solar hybrid bus has been designed and analysed comprehending the addition of solar panels in the powertrain and the increased weight due to the same. Use of hybrid technology reduces the emissions up to 30-35% but with solar energy, emissions can be reduced up to 55%. Comparison between petrol, diesel and CNG is done to justify the use of CNG as the engine fuel. Comparisons are also carried out between Monocrystalline and Polycrystalline solar panels and the one with the more efficiency and power to weight ratio is selected i.e. Monocrystalline solar panels. Monocrystalline panels produce 120- 180 Watt per meter square against 50-80 Watt per meter square of power produced in case of Polycrystalline panels. Ambiguity in the use of either Ni-MH or Li-ion battery in hybrid buses is resolved. Selection of electric motor with 350 hp, 1000 Nm torque and 3450 rpm yields 0.8 m/s 2 maximum acceleration, 74.74 km/hr maximum velocity and reduction gearbox of gear ratio between 2:1 to 3:1.
Two-Mode Hybrid Transmission is applied for 2MT70 transmission which includes a simple planetary gear set, a compound planetary gear set, four consisting clutches, and two electric motor/generators, as shown in Figure 1.With the activation of clutches, the transmission could operates in two different electric variable transmission modes (EVT-1 and EVT-2) and four fixed gear (FG-1 ~ 4)[1,2].
A fuzzy logic control strategy for parallel HEV was proposed to manage the powertrain system. The fuzzy rules table was designed based on knowledge of expert, while parameters of fuzzy MFs were optimized by adopting GA. The goal of optimization was to minimize energy cost and emissions. In order to consider the energy consumption of the battery, the variance between initial SOC and final SOC of the battery considered in objective function. The controller parameters were optimized over UDDS and NEDC drive cycles. This approach improved the energy cost about 16%, and also reduced the emissions by 32%, since the vehicle performance didn’t sacrifice. The tuned FLC also kept the battery SOC within a suitable range, and IC engine operated at fuel efficient region. The proposed genetic-fuzzy approach is a robust approach which has potential to be used in the control unit of a real vehicle.
More than 200 million people, live in rural areas without access to grid-connected power. In India, over 80,000 villages remain to be un-electrified and particularly in the state of Tamil Nadu, about 400 villages (with 63% tribes) are difficult to supply electricity due to inherent problems of location and economy . The costs to install and service the distribution lines are considerably high for remote areas. Also there will be a substantial increase in transmission line losses in addition to poor power supply reliability. Like several other developing countries, India is characterized by severe energy deficit. In most of the remote and non-electrified sites, extension of utility grid lines experiences a number of problems such as high capital investment, high lead time, low load factor, poor voltage regulation and frequent power supply interruptions. There is a growing interest in harnessing renewable energy sources since they are naturally available, pollution free and inexhaustible. It is this segment that needs special attention and hence concentrated efforts are continually provided in implementing standalone PV, wind, bio-diesel generator and integrated systems at sites that have a large potential of either solar, wind or both. Traditionally, electrical energy for remote villages has been derived from diesel generators characterized by high reliability, high running costs, moderate efficiency and high maintenance. Hence, a convenient, cost-effective and reliable power supply is an essential factor in the development of any rural area. It is a critical factor in the development of the agro industry and commercial operations, which are projected to be the core of that area’s economy. At present, standalone solar photovoltaic and wind systems have been promoted around the globe on a comparatively larger scale. These independent systems cannot provide continuous source of energy, as they are seasonal. For example, standalone solar photovoltaic energy system cannot provide reliable power during non-sunny days. The standalone wind system cannot satisfy constant load demands due to significant fluctuations in the magnitude of wind speeds from hour to hour throughout the year. Therefore, energy storage systems will be required for each of these systems in order to satisfy the power demands. Usually storage system is expensive and the size has to be reduced to a minimum possible for the renewable energy system to be cost effective. Hybrid power systems can be used to reduce energy storage requirements.
Findings: The proposed versatile fluffy controller based MPPT strategy will improve the power yield from the power plants and the proposed controller can be utilized to give heartiness and upgrade the execution of matrix. The fluffy controlling system likewise discovered proficient for constantly shifting burdens. The proposed demonstrate is executed and examined utilizing MATLAB/Simulink programming.
Simulations have been carried out for the exemplary HEV vehicle, whose characteristics are summarized in table I, and the Mugello circuit. Figure 4 shows the circuit and also the calculated optimal trajectory, speed and accelera- tion. In order to better understand the significance of the battery power boost and its optimal utilization, the vehicle performances with and without the battery are compared. The figure highlights that the boost (blue line) slightly increases acceleration and top speed, leading to a difference in the lap time of 189.19 s versus 191.24 s (i.e. +2.05 s) when the battery is disabled. Secondly, the figure shows that speed and acceleration are equal both at the beginning and at the end of the lap, according to the imposed cyclic boundary conditions. While acceleration is limited by engine battery power, deceleration is limited by tire adherence. The latter is depicted in Figure 5 in terms of the lateral force to tire load ratio vs longitudinal force to tire load ratio, for both tires. In particular this picture shows that the optimal maneuver makes large utilization of combined longitudinal and lateral
 Sunil Kumar , ‘Research Work for Optimization and Effect of WEDM Cutting Process Parameters on Performance Measures’, International Journal for Research in Applied Science & Engineering Technology, vol 8, 2017,pp 105-121.
of bus schedule frequency, where the fittest frequency could be easily calculated (Mohring, 1972). Hurdle (1973) devised a schedule to minimize the total cost, including passenger waiting time, and vehicle operation cost using fluid flow model and found the optimal solutions for a number of hypothetical frequency. Since the demand for high quality bus service increased, Marques et al. (1996) introduced a notion of flexible and dynamic public transport schedule, and the system comprehensively analyzed service supply, demand and network data to reschedule the so-called SUPERBUS. Feasibility evaluation of the technology, user- acceptance and socioeconomics for SUPERBUS was also included in the study. Mekkaoui et al. (2000) used an explicit traveler choice model, which assumed bus riders select the solution to minimize the cost incurred by traveling earlier or later than their ideal schedule time, to obtain the desirable solution. Ceder (2005, 2007) introduced four different methods in determining a timetable based on a range of data collection techniques. Bai et al. (2013) analyzed bus scheduling method including big interval departure, time in coordination, adopted three synchronization methods and obtained inhomogeneous departure intervals.
are modeled using structure diagrams like the Internal Block Diagram in SysML . The modeling of functional system structures is done applying elements from the Contact-&Channel-Model (C&C-M) for SysML, which also has been developed at the IPEK . Coevally, this model is improved and applied into an industrial environment for the first time. Using this C&C-M for SysML enables modeling of interfaces as different types of input and output values, which are there called Working Surfaces. Giving an example, interfaces of a vehicle to non-technical systems are the human-machine-interface (cockpit) or influencing weather conditions (temperature, humidity etc.). Interfaces to technical systems may appear for communication systems like GPS or radio, but also for radar sensor systems like adaptive cruise control (ACC). In case of developing a subsystem within a vehicle assembly (i.e. powertrain), manifold interfaces like chassis mounting, energy supply or drive torque transmission to the wheels appear.
Dongfeng Commercial Vehicles (DFCV) is develop- ing powertrain controls for a hybrid light truck. To support this development, a virtual integration plat- form is being implemented, using Modelica models and Functional Mock-up Units (FMUs) for the en- gine/EMS, gearbox, MCU/e-motors, driveline, tyres and longitudinal dynamics. Simulink models and/or c-code of the Hybrid Control Unit (HCU) and Transmission Control Unit (TCU) are also integrat- ed in the platform to achieve closed-loop simulation. The virtual integration allows reproducing accurately the overall vehicle behavior and is used for optimiza- tion of gearshifts, hybrid mode switches and hybrid drive strategies.
Future work may include additional parameter estimation techniques, such as the hybridoptimization technique mentioned in , to improve the performance of Tremblay’s model parameterization. The performances of the GA, the PSO, and the QPSO parameter estimation techniques could be further enhanced by optimizing the algorithms’ parameters, such as the cognitive and social learning rates in the PSO algorithm and the contraction-expansion coefficient in the QPSO algorithm. The weighting function could also be adjusted to improve the convergence speed and accuracy of the estimated results. Finally, additional simulations could be performed using a larger particle/chromosome size and a higher number of generations.
While the secondary selection in NSGA-II is based on crowding distances, the one in NSGA-III is based on the niching counts which are calculated by associating the can- didate solutions with the closest reference line specified by each weight vector. The motivation behind such a niching based selection is that in many-objective optimization, where the candidate solutions are sparsely distributed, setting up fixed references is more efficient in diversity management than dynamically adapting the distribution of the candidate solutions according to the Euclidean distances between them. Apart from the dominance based selection and the niching based selection, another important component in NSGA-III is the normalization (Step 9 in Algorithm 2). The normalization process in NSGA-III is designed to normalize the objective function values into the same range such that the candidate solutions are still uniformly distributed with respect to the weight vector even on a non-normalized PF where the objec- tive function values are scaled to different ranges.