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نتیجه جستجو - خودروهای برقی هیبریدی

تعداد مقالات یافته شده: 6
ردیف عنوان نوع
1 A Non-Convex Control Allocation Strategy as Energy-Efficient Torque Distributors for On-Road and Off-Road Vehicles
یک استراتژی تخصیص کنترل غیر محدب به عنوان توزیع کننده گشتاور مقرون به صرفه برای وسایل نقلیه جاده ای و خارج از جاده-2020
A Vehicle with multiple drivetrains, like a hybrid electric one, is an over-actuated system that means there is an infinite number of combinations of torques that individual drivetrains can supply to provide a given total torque demand. Energy efficiency is considered as the secondary objective to determine the optimum solution among these feasible combinations. The resulting optimisation problem, which is nonlinear due to the multimodal operation of electric machines, must be solved quickly to comply with the stability requirements of the vehicle dynamics. A theorem is developed for the first time to formulate and parametrically solve the energyefficient torque distribution problem of a vehicle with multiple different drivetrains. The parametric solution is deployable on an ordinary electronic control unit (ECU) as a small-size lookup table that makes it significantly fast in operation. The fuel-economy of combustion engines, load transformations due to longitudinal and lateral accelerations, and traction efficiency of the off-road conditions are integrated into the developed theorem. Simulation results illustrate the effectiveness of the provided optimal strategy as torque distributors of on-road and off-road electrified vehicles with multiple different drivetrains.
Keywords: Traction efficiency | Control allocation | Energy management strategies | Hybrid electric vehicles | Power loss | Multiple drivetrains
مقاله انگلیسی
2 Optimization & validation of Intelligent Energy Management System for pseudo dynamic predictive regulation of plug-in hybrid electric vehicle as donor clients
بهینه سازی و اعتبار سنجی سیستم مدیریت انرژی هوشمند برای تنظیم پیش بینی شبه دینامیکی پلاگین در خودروهای برقی هیبریدی به عنوان مشتری دهنده-2020
In developing countries, policies for discarding the existing Internal Combustion (IC) Engine vehicles for faster adoption of Electric Vehicles’ not only creates burden on the existing power grid but also is impractical. The conversion of Conventional IC Engine based Online Taxis or public transport vehicles into Plug-in Hybrid Electric Vehicles donor clients, to participate in Vehicle to Grid & Vehicle to Vehicle power transfer model, is the solution. These vehicles would not only have emissions within compliance standards but would also reduces the load on the power grid meanwhile making an income through power transfer. The Intelligent Energy Management System (IEMS) developed makes use of a Non Dominated Sorting Genetic Algorithm (NSGA-II) based Pseudo dynamic predictive regulation approach on the powertrain to optimize the emissions, fuel cost and traction battery SoC. If the vehicle intends to participate in power transfer, the IEMS would predetermine the amount of SoC that would be used for an upcoming journey using Global Positioning System(GPS) data interconnected with a server unit which enables the IEMS to optimize the operating conditions of the vehicle. The modelled IEMS performance is tested for a given driving cycle with varying traffic levels on a virtual simulation environment using the IPG CarMaker software. A prototype with a 150 cc, 7.5 kW IC engine integrated to a 3 kW BLDC traction motor is developed and the response to the predictive model is evaluated and found to provide 27.66%, 13.73% and 7.72% equivalent energy to micro grid for low, medium and high criticality conditions for the user.
Keywords: Vehicle to grid | NSGA-II optimization | State of charge | Emission | GPS | Real-time validation
مقاله انگلیسی
3 Energy management of hybrid vehicles with state constraints: A penalty and implicit Hamiltonian minimization approach
مدیریت انرژی وسایل نقلیه هیبریدی با محدودیت های دولت: رویکردحداقل سازی همیلتونی ضمنی و مجازاتی -2020
When designing hybrid vehicles, the energy management is formulated as an optimal control problem. The Pontryagin’s minimum principle represents a powerful methodology capable of solving the energy management offline. Moreover, the Pontryagin’s minimum principle has been proved useful in the derivation of online energy management algorithms, such as the equivalent consumption minimization strategy. Nevertheless, difficulties on the application of the Pontryagin’s minimum principle arise when state constraints are included in the definition of the problem. A possible solution is to combine the Pontryagin’s minimum principle with a penalty function approach. This is done by adding functions to the Hamiltonian, which increase the value of the Hamiltonian whenever the optimal trajectory violates its constraints. However, the addition of penalty functions to the Hamiltonian makes it harder to compute its minimum. This work proposes an effective penalty approach through an implicit Hamiltonian minimization. The proposed method is applied to solve the energy management for a hybrid electric vehicle modeled as a mixed input-state constrained optimal control problem with two states: the battery temperature and state-of-energy. It is demonstrated to be up to 46 times faster than the dynamic programming method while taking benefits of state-of-the-art boundary value problem solvers and avoiding any issue related to state quantization.
Keywords: Energy management | Hybrid electric vehicles | Pontryagin’s minimum principle | Mixed input-state constraints | Penalty function approach
مقاله انگلیسی
4 Improvement of ultracapacitors-energy usage in fuel cell based hybrid electric vehicle
بهبود استفاده از انرژی ماورا بنفش در خودروی برقی هیبریدی مبتنی بر سلول سوختی-2020
Hybrid electric power systems based on fuel cell stack and energy storage sources like batteries and ultracapacitors are a plausible solution to vehicle electrification due to their balance between acceleration performance and range. Having a high degree of hybridization can be advantageous, considering the different characteristics of the power sources. Some parameters to be considered are: specific power and energy, energy and power density, lifetime, cost among others. Ultracapacitors (UC) are of particular interest in electric vehicle applications due to its high-power capability, which is commonly required during acceleration. UCs are commonly used without a power electronics interface due to the high-power processing requirement. Although connecting UCs directly to the DC bus, without using a power converter, presents considerable advantages, the main disadvantage is related to the UC energy-usage capability, which is limited by constant DC bus control. This paper proposes a novel energy-management strategy based on a fuzzy inference system, for fuel-cell/battery/ultracapacitor hybrid electric vehicles. The proposed strategy is able to control the charge and discharge of the UC bank in order to take advantage of its energy storage capability. Experimental results show that the proposed strategy reduces the waste of energy due to dynamic brake in 14%. This represents a reduction in energy consumption from 218 Wh/km to 192 Wh/km for the same driving conditions. By using the proposed energy management strategy, the estimated fuel efficiency in miles per gallon equivalent was also increase from 96 mpge to 109 mpge.
Keywords: PEMFC | Hybrid electric vehicles | Energy management | Ultracapacitors
مقاله انگلیسی
5 A robust online energy management strategy for fuel cell/battery hybrid electric vehicles
یک استراتژی مدیریت انرژی آنلاین قوی برای خودروهای برقی هیبریدی سلول / باتری-2020
Traditional optimization-based energy management strategies (EMSs) do not consider the uncertainty of driving cycle induced by the change of traffic conditions, this paper proposes a robust online EMS (ROEMS) for fuel cell hybrid electric vehicles (FCHEV) to handle the uncertain driving cycles. The energy consumption model of the FCHEV is built by considering the power loss of fuel cell, battery, electric motor, and brake. An offline linear programming-based method is proposed to produce the benchmark solution. The ROEMS instantaneously minimizes the equivalent power of fuel cell and battery, where an equivalent efficiency of battery is defined as the efficiency of hydrogen energy transforming to battery energy. To control the state of charge of battery, two control coefficients are introduced to adjust the power of battery in objective function. Another penalty coefficient is used to amend the power of fuel cell, which reduces the load change of fuel cell so as to slow the degradation of fuel cell. The simulation results indicate that ROEMS has good performance in both fuel economy and load change control of fuel cell. The most important advantage of ROEMS is its robustness and adaptivity, because it almost produces the optimal solution without changing the control parameters when driving cycles are changed.
Keywords: Fuel cell | Hybrid electric vehicles | Online energy management strategy | Robustness | Uncertaint
مقاله انگلیسی
6 Energy management strategy for plug-in hybrid electric vehicle integrated with vehicle-environment cooperation control
استراتژی مدیریت انرژی برای پلاگین در خودروهای برقی هیبریدی یکپارچه با کنترل همکاری خودرو-محیط-2020
Energy management strategies have been proven to be instrumental in fully realizing the potential of plug-in hybrid electric vehicles (PHEVs). This paper proposes an improved adaptive equivalent consumption minimization strategy (IA-ECMS). In an IA-ECMS, the equivalence factor (EF) can be tuned in real time due to integration with the results of the vehicle-environment cooperative control. This study’s main contributions are twofold. First, a novel A-ECMS is developed, in which the EF tuning method is carefully designed based on the results of a correlation study. The study results reveal that EF is determined by the future driving behaviour and the current component status. To ascertain the future driving behaviour, a method based on participatory sensing data (PSD) is used to implement the vehicleenvironment cooperative control. Second, a comparative study of the IA-ECMS and the energy management strategy based on the existing model of predictive control (MPC) is performed. The comparison results show that the application process of the IA-ECMS is similar to that of the MPC-based method except for two main differences. The simulation results demonstrate that the presented IA-ECMS approach could outperform in fuel economy the conventional A-ECMS (CA-ECMS) method.
Keywords: Plug-in hybrid electric vehicles | Adaptive equivalent consumption | minimization strategy | Equivalence factor | Model predictive control | Vehicle-environment cooperative control
مقاله انگلیسی
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