Control Strategy Optimization for a Parallel Hybrid Electric Vehicle

The efficiency improvement of parallel hybrid electric vehicles (HEVs) is strongly dependent on how the supervisory control of a vehicle determines the power split between the internal combustion engine (ICE) and the electric motor of the vehicle. This paper presents a classification of current supervisory control techniques with distinction between dynamic and static control methods; a description of the simulation software ADvanced Vehicle SimulatOR (ADVISOR) with Matlab Simulink for simulation of a rule-based control strategy, and proposed optimization methods

Single-Phase Bidirectional AC-DC Converters for Plug-in Hybrid Electric Vehicle Applications

Plug-in hybrid electric vehicles (PHEVs) are specialized hybrid electric vehicles that have the potential to obtain enough energy for average daily commuting from batteries. These batteries would be charged from the power grid and would thus allow for a reduction in the overall petroleum consumption. To implement the plug-in function, a single phase bidirectional AC-DC converter interfacing with the grid is essential. The implementation of a bidirectional AC-DC converter can allow for battery recharge from the grid, battery energy injection to the AC grid, and battery energy for AC power stabilization. In this paper, the basic requirements and specifications for PHEV bidirectional AC-DC converter designs are presented. Generally, there are two types of topologies used for PHEVs: an independent topology and a combination topology that utilizes the drive motor\u27s inverter. Evaluations of the two converter topologies are analyzed in detail. The combination topology analysis is emphasized because it has more advantages in PHEVs, in respect to savings in cost, volume and weight

Parametric Study of Alternative EV1 Powertrains

The General Motors (GM) EV1 is an electric vehicle originally powered by either a PbA or NiMh battery pack. This paper examines the possibility of alternative powertrain configurations. These alternatives include an ultracapacitor (UC) storage system, fuel cell system with UC storage, and a fuel cell system with a NiMh battery pack. The configurations were simulated using ADVISOR. Parametric tests were performed by varying the size of the energy storage systems. The study of these combinations is followed by an examination of the current art of the hybrid energy storage topologies used to combine battery and ultracapacitor storage. These topologies include passive parallel, active parallel, cascade parallel, and multi-input bidirectional converter

Study on the Effects of Battery Capacity on the Performance of Hybrid Electric Vehicles

Hybrid electric vehicles are gaining a significant presence in the auto market. However, the present day hybrid electric vehicles mostly use battery as a secondary source of power. If the battery were to be used as a primary source of power then the battery capacity is one of the important features in the design of a hybrid electric vehicle. Hybrid electric vehicles which are powered by more than one energy source have to follow a good energy management strategy to provide the best fuel economy in all situations. This paper presents a comprehensive study of the effect of variation of the energy storage system size on the fuel economy of a hybrid electric vehicle and the important design criteria involved in the design of the energy storage system. Simulations carried out using ADVISOR software show that increase in battery capacity alone cannot improve the fuel economy

Development of a fuel cell plug-in hybrid electric vehicle and vehicle simulator for energy management assessment

This dissertation offers a description of the development of a fuel cell plug-in hybrid electric vehicle focusing on the propulsion architecture selection, propulsion system control, and high-level energy management. Two energy management techniques have been developed and implemented for real-time control of the vehicle. The first method is a heuristic method that relies on a short-term moving average of the vehicle power requirements. The second method utilizes an affine function of the short-term and long-term moving average vehicle power requirements. The development process of these methods has required the creation of a vehicle simulator capable of estimating the effect of changes to the energy management control techniques on the overall vehicle energy efficiency. Furthermore, the simulator has allowed for the refinement of the energy management methods and for the stability of the method to be analyzed prior to on-road testing. This simulator has been verified through on-road testing of a constructed prototype vehicle under both highway and city driving schedules for each energy management method. The results of the finalized vehicle control strategies are compared with the simulator predictions and an assessment of the effectiveness of both strategies is discussed. The methods have been evaluated for energy consumption in the form of both hydrogen fuel and stored electricity from grid charging --Abstract, page iii

Designing Efficient Hybrid Electric Vehicles

Hybrid electric vehicles (HEVs) are increasingly gaining popularity due to their lower fuel consumption. Current hybrid vehicles mostly use their battery or the energy storage system (ESS) as a secondary source of power. If the ESS were to be used as a primary source of power, then the ESS size would be one of the important features in the design of an HEV. In addition, HEVs have to employ an intelligent energy management strategy to provide the best fuel economy in all driving situations. This article presents an investigation on the effect of the variation of the ESS size on the fuel economy of an HEV and the important design criteria involved in the design of the ESS. Simulations carried out using advanced vehicle simulator (ADVISOR) software show that fuel economy is not linearly related to ESS size and therefore the ESS needs to be designed based on the average daily driving distance and the driver behavior

Supervisory Control Development of a Fuel Cell Plug-in Hybrid Electric Vehicle

The design of a supervisory control system for a fuel cell plug-in hybrid vehicle is similar to that of an internal combustion engine plug-in hybrid. However, the desire to maximize the all electric range is lessened due to reduced petroleum usage and tail-pipe emissions of the fuel cell system. This paper presents a control strategy which uses a fuel cell at a low but highly efficient power level during charge depleting operation. Once the charge sustaining operating conditions are achieved the fuel cell system switches to a higher average power operating point. The developed control strategy is simulated using the Powertrain System Analysis Toolkit (PSAT)

A Framework to Analyze the Requirements of a Multiport Megawatt-Level Charging Station for Heavy-Duty Electric Vehicles

Widespread adoption of heavy-duty (HD) electric vehicles (EVs) will soon necessitate the use of megawatt (MW)-scale charging stations to charge high-capacity HD EV battery packs. Such a station design needs to anticipate possible station traffic, average and peak power demand, and charging/wait time targets to improve throughput and maximize revenue-generating operations. High-power direct current charging is an attractive candidate for MW-scale charging stations at the time of this study, but there are no precedents for such a station design for HD vehicles. We present a modeling and data analysis framework to elucidate the dependencies of a MW-scale station operation on vehicle traffic data and station design parameters and how that impacts vehicle electrification. This framework integrates an agent-based charging station model with vehicle schedules obtained through real-world vehicle telemetry data analysis to explore the station design and operation space. A case study applies this framework to a Class 8 vehicle telemetry dataset and uses Monte Carlo simulations to explore various design considerations for MW-scale charging stations and EV battery technologies. The results show a direct correlation between optimal charging station placement and major traffic corridors such as cities with ports, e.g., Los Angeles and Oakland. Corresponding parametric sweeps reveal that while good quality of service can be achieved with a mix of 1.2-megawatt and 100-kilowatt chargers, the resultant fast charging time of 35–40 min will need higher charging power to reach parity with refueling times

Grid Impact Analysis and Mitigation of En-Route Charging Stations for Heavy-Duty Electric Vehicles

This paper presents a comprehensive grid impact analysis design and corresponding mitigation strategies for heavy-duty electric vehicle (EV) charging stations. The charging load of heavy-duty charging station can reach several megawatts, which could induce adverse impacts on the distribution grid if not effectively mitigated. To analyze the impacts and provide corresponding solutions, we select four representative distribution systems—including both single-feeder cases and a multi-feeder case—and design thorough test metrics for the impact analysis. The charging load profiles used in the analysis are derived from realistic conventional heavy-duty vehicle travel data. Based on the analysis results, charging stations are placed at three different representative locations in each distribution system: best, good, and worst locations. Mitigation strategies using a combination of smart charger functionality, on-site photovoltaic (PV) generation, and on-site energy storage (ES) are proposed and tested. A sizing method is also proposed to find the optimal PV-ES-charger capacity that minimizes the capital cost

A Framework to Analyze the Requirements of a Multiport Megawatt-Level Charging Station for Heavy-Duty Electric Vehicles

Widespread adoption of heavy-duty (HD) electric vehicles (EVs) will soon necessitate the use of megawatt (MW)-scale charging stations to charge high-capacity HD EV battery packs. Such a station design needs to anticipate possible station traffic, average and peak power demand, and charging/wait time targets to improve throughput and maximize revenue-generating operations. High-power direct current charging is an attractive candidate for MW-scale charging stations at the time of this study, but there are no precedents for such a station design for HD vehicles. We present a modeling and data analysis framework to elucidate the dependencies of a MW-scale station operation on vehicle traffic data and station design parameters and how that impacts vehicle electrification. This framework integrates an agent-based charging station model with vehicle schedules obtained through real-world vehicle telemetry data analysis to explore the station design and operation space. A case study applies this framework to a Class 8 vehicle telemetry dataset and uses Monte Carlo simulations to explore various design considerations for MW-scale charging stations and EV battery technologies. The results show a direct correlation between optimal charging station placement and major traffic corridors such as cities with ports, e.g., Los Angeles and Oakland. Corresponding parametric sweeps reveal that while good quality of service can be achieved with a mix of 1.2-megawatt and 100-kilowatt chargers, the resultant fast charging time of 35–40 min will need higher charging power to reach parity with refueling times