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Fuel consumption reduction on medium-duty tactical truck has and continues to be a significant initiative for the U.S. Army. The Crankshaft-Integrated-Starter-Generator (C-ISG) is one of the parallel hybrid propulsions to improve the fuel economy. The C-ISG configuration is attractive because one electric machine can be used to propel the vehicle, to start the engine, and to be function as a generator. The C-ISG has been implemented in one M1083A1 5-ton tactical cargo truck. This paper presents the experimental assessments of the C-ISG hybrid truck characteristics. The experimental assessments include all electric range for on- and off-road mission cycles and fuel consumption for the high voltage battery charging. Stationary tests related to the charging profile of the battery pack and the silent watch time duration is also conducted.

Fuel cells are a promising energy source on account of their high efficiency and low emissions. Proton exchange membrane fuel cells (PEMFC) are clean and environmental-friendly power sources, which can become future energy solutions especially for transport vehicles. They exhibit good energy efficiency and high power density per volume. Working at low temperatures (<90°C), hydrogen fuelled proton exchange membrane fuel cells (PEMFCs) are identified as promising alternatives for powering autos, houses and electronics. At the middle of the proton exchange membrane (PEM) fuel cell is the membrane electrode assembly (MEA). The MEA consists of a proton exchange membrane, catalyst layers, and gas diffusion layers (GDL). However, most of the researchers have already mentioned that PEMFC are not competitive enough to rechargeable lithium ion battery with respect to price because of the rare metal used such as platinum in it.

Battery electric vehicles possess great potential for decreasing lifecycle costs in medium-duty applications, a market segment currently dominated by internal combustion technology. Characterized by frequent repetition of similar routes and daily return to a central depot, medium-duty vocations are well positioned to leverage the low operating costs of battery electric vehicles. Unfortunately, the range limitation of commercially available battery electric vehicles acts as a barrier to widespread adoption. This paper describes the National Renewable Energy Laboratory's collaboration with the U.S. Department of Energy and industry partners to analyze the use of small hydrogen fuel-cell stacks to extend the range of battery electric vehicles as a means of improving utility, and presumably, increasing market adoption.

This paper presents 3D finite element analysis performed for a composite cylindrical tank made of 6061-aluminum liner overwrapped with carbon fibers subjected to a burst internal pressure of 1610 bars. As the service pressure expected in these tanks is 700 bars, a factor of safety of 2.3 is kept the same for all designs. The optimal design configuration of such high pressure storage tanks includes an inner liner used as a gas permeation barrier, geometrically optimized domes, inlet/outlet valves with minimum stress concentrations, and directionally tailored exterior reinforcement for high strength and stiffness. Filament winding of pressure vessels made of fiber composite materials is the most efficient manufacturing method for such high pressure hydrogen storage tanks. The complexity of the filament winding process in the dome region is characterized by continually changing the fiber orientation angle and the local thickness of the wall.

This paper describes the system architecture together with control and diagnostics features of an indigenously developed electric vehicle controller for Light Commercial Vehicle. The key functions of vehicle controller include power management, driveline controls, regeneration and vehicle mode controls. In particular this paper presents vehicle's operational strategy in economy, normal and performance modes based on the vehicle speed and SOC. It also has feature to enable vehicle operation in reduced performance mode at low battery voltages. The battery fault predictor algorithm is also described in detail that is used to control discharge current to prevent sudden dip in SOC and to increase battery life. The vehicle control strategy is modeled & simulated using MATLAB™ environment and results for a specific test case are validated with embedded controllers-in-the-loop in a test-bench environment.

IEEE Standard 1609.2-2013, Security Services for Applications and Management Messages for Wireless Access in Vehicular Environments (WAVE), specifies its data structures and encoding using a proprietary language based on that used in the Internet Engineering Task Force (IETF)'s Transport Layer Security (TLS) specification. This approach is believed to allow fast encoding and decoding, but is non-standard, is not proved to be complete, lacks automatic tools for generation of codecs, and is difficult to extend. For these reasons, the 1609 Working Group approved the use of Abstract Syntax Notation 1 (ASN.1) for future versions of 1609.2, so long as ASN.1 did not significantly degrade performance. This paper is the first publication of the results of a performance analysis carried out to determine whether ASN.1-based encoding was in fact acceptable.

The main objective of this study is to reduce the aerodynamic drag of tractor-trailer combinations used in the forest industry. In most cases, logging trucks on their return trips are usually travelling in unloaded conditions with upright stakes, which add drag. CFD and wind tunnel testing suggested a drag reduction of up to 35% with no upright stakes, which corresponds to 17% in fuel savings in unloaded conditions. One of the proposed fuel reduction concepts was therefore to have foldable stakes so that the stakes could fold down into a horizontal position while travelling in unloaded conditions. Fuel savings of 15% for a vehicle with stakes in the horizontal position were confirmed with track testing when compared to the fuel consumption of a vehicle with stakes in the vertical position. The coastdown test indicated 28% reduction in drag. The difference in drag reduction between the coastdown test and initial simulation was due to stake size and profile.

Many aspects of battery electric vehicles are very challenging from the engineering point of view in terms of safety, weight, range, and drivability. Commercial vehicle engines are often subjected to high loads even at low speeds and this can lead to an intense increment of the battery pack temperature and stress of the cooling system. For these reasons the optimal design of the battery pack and the relative cooling system is essential. The present study deals with the challenge of designing a battery pack that satisfies both the conditions of lowest weight and efficient temperature control. The trade-off between the battery pack size and the electrical stress on the cells is considered. The electric system has the aim to substitute a 3.0 liters compression ignition engine mainly for commercial vehicles.

The lightweight design of a vehicle can save manufacturing costs and reduce greenhouse gas emissions. For the off-road vehicle and truck, the chassis frame is the most important load-bearing assembly of the separate frame construction vehicle. The frame is one of the most assemblies with great potential to be lightweight optimized. However, most of the vehicle components are mounted on the frame, such as the engine, transmission, suspension, steering system, radiator, and vehicle body. Therefore, boundaries and constraints should be taken into consideration during the optimal process. The finite element (FE) model is widely used to simulate and assess the frame performance. The performance of the frame is determined by the design parameters. As one of the largest components of the vehicle, it has a lot of parameters. To improve the optimum efficiency, sensitivity analysis is used to narrow the range of the variables.

Electric vehicles have a limitation of limited range and long charging time. Energy optimization plays a very crucial role in determining the range of an electric vehicle. The innovative system proposed here gives the opportunity to reduce energy wastage and efficiently direct the electrical energy to improve the driving range of a 9 meter AC electric bus. The high voltage air conditioner unit alone consumes more than 40% of the electrical energy stored in the traction battery which reduces the driving range of the electric bus drastically. The proposed system optimizes the air conditioner utilization to direct cool air only in areas where passengers are present. Buses do not always run on full capacity, when there are less number of people in the bus the system detects the locations of the passengers using sensors and occupant detection algorithm, this enables the controller to identify the areas where cooling has to be focused and where cooling can be reduced or stopped.

The public transport in India is gradually shifting towards electric mobility. Long range in electric mobility can be served with High Voltage Battery (HVB), but HVB can sustain for its designed life if it’s maintained within a specific operating temperature range. Appropriate battery thermal management through Battery Cooling System (BCS) is critical for vehicle range and battery durability This work focus on two aspects, BCS sizing and its coolant flow optimization in Electric bus. BCS modelling was done in 1D CAE software. The objective is to develop a model of BCS in virtual environment to replicate the physical testing. Electric bus contain numerous battery packs and a complex piping in its cooling system. BCS sizing simulation was performed to keep the battery packs in operating temperature range.

Electric Vehicles (EVs), with its inherent advantage of zero tailpipe emissions, are gaining importance because of aggressive push from government not only to reduce air pollution but also to reduce dependency of fossil fuel. EVs and necessary charging infrastructure along with ‘connected’ technology is redefining mobility. Considering the fast growing EV market, it becomes important for an EV Powertrain Architect to design and develop a powertrain solution having low engineering efforts and satisfying business, market and regulatory requirements at a competitive price. This paper presents a compact, flexible, convenient and smart featured simulation tool for an EV Powertrain Architect for estimating the specifications of key powertrain components such as traction battery and electric motor. The proposed tool takes into consideration the end-user as well as the regulatory requirements of range, maximum speed, acceleration and gradeability.

This paper addresses scheduling of quantized power levels (including part load operation and startup/shutdown periods) for a propane powered solid oxide fuel cell (SOFC) hybridized with a lithium-ion battery for a tracked mobile robot. The military requires silent operation and long duration missions, which cannot be met by batteries alone due to low energy density or with combustion engines due to noise. To meet this need we consider an SOFC operated at a few discrete power levels where maximum system efficiency can be achieved. The fuel efficiency decreases during transients and resulting thermal gradients lead to stress and degradation of the stack; therefore switching power levels should be minimized. Excess generated energy is used to charge the battery, but when it’s fully charged the SOFC should be turned off to conserve fuel.

Turbulence is known to influence the aerodynamic and aeroacoustic performance of ground vehicles. What is not thoroughly understood are the characteristics of turbulence that influence this performance and how they can be applied in a consistent manner for aerodynamic design and evaluation purposes. Through collaboration between Transport Canada and the National Research Council Canada (NRC), a project was undertaken to develop a system for generating road-representative turbulence in the NRC 9 m Wind Tunnel, named the Road Turbulence System (RTS). This endeavour was undertaken in support of a larger project to evaluate new and emerging drag reduction technologies for heavy-duty vehicles. A multi-stage design process was used to develop the RTS for use with a 30% scale model of a heavy-duty vehicle in the NRC 9m Wind Tunnel.

This study investigates the use of machine learning methods for the selection of energy storage devices in military electrified vehicles. Powertrain electrification relies on proper selection of energy storage devices, in terms of chemistry, size, energy density, and power density, etc. Military vehicles largely vary in terms of weight, acceleration requirements, operating road environment, mission, etc. This study aims to assist the energy storage device selection for military vehicles using the data-drive approach. We use Machine Learning models to extract relationships between vehicle characteristics and requirements and the corresponding energy storage devices. After the training, the machine learning models can predict the ideal energy storage devices given the target vehicles design parameters as inputs. The predicted ideal energy storage devices can be treated as the initial design and modifications to that are made based on the validation results.

Overall cycle time and prototype testing are significantly decreased by assessment of cooling module performance in the design stage itself. Hence, Front End Cooling and Thermal Management are essential components of the vehicle design process. Performance of the cooling module depends upon a variety of factors like frontal opening, air flow, under-hood sub-systems, module positioning, front grill design, fan operation. Effects of design modifications on the engine cooling performance are quantified by utilizing computational fluid dynamics (CFD) tool FluentTM. Vehicle frontal configuration is captured in the FE model considering cabin, cargo and underbody components. Heat Exchanger module is modelled as a porous medium to simulate the fluid flow. Performance data for the Heat Exchanger module is generated using the 1D KuliTM software. In this paper, CFD simulation of Front End Cooling is performed for maximum torque and maximum power operating conditions.

The temperature distribution is studied theoretically in a battery module stacked with 12 high-power Li-ion pouch cells. The module is cooled indirectly with ambient air through aluminum heat-sink plates or cooling plates sandwiched between each pair of cells in the module. Each of the cooling plates has an extended cooling fin exposed in the cooling air channel. The cell temperatures can be controlled by changing the air temperature and/or the heat transfer coefficient on the cooling fin surfaces by regulating the air flow rate. It is found that due to the high thermal conductivity and thermal diffusivity of the cooling plates, heat transfer of the cooling plate governs the cell temperature distribution by spreading the cell heat over the entire cell surface. Influence of thermal from the cooling fins is also simulated.

Architecting and integrating commercial hybrid electric vehicles (HEV) is a long and labor intensive process which is unique every time. The challenge intensifies when one attempts to create an HEV capable of engine-off operation. In this case, electrical power needs to be supplied to devices which are normally powered by the engine accessory belt. These devices are referred to as e-accessories. To address the issue of time to market and reduce vehicle integration burden, a plug-and-play architecture for connecting e-accessories has been developed. The Flexible High Voltage DC System is analogous to a USB hub on a PC and serves to provide power, control and communication to e-accessories such as electrified power steering, electrified brakes and electrified HVAC.

Electrification and hybridization show great potential for improving fuel economy and reducing emission in heavy-duty vehicles. However, high battery cost is unavoidable due to the requirement for large batteries capable of providing high electric power for propulsion. The battery size and cost can be reduced with advanced battery control strategies ensuring safe and robust operation covering infrequent extreme conditions. In this paper, the impact of such a battery control strategy on battery sizing and fuel economy is investigated under various military and heavy-duty driving cycles. The control strategy uses estimated Li-ion concentration information in the electrodes to prevent battery over-charging and over-discharging under aggressive driving conditions. Excessive battery operation is moderated by adjusting allowable battery power limits through the feedback of electrode-averaged Li-ion concentration estimated by an extended Kalman filter (EKF).

Ideal operation temperatures for Li-ion batteries fall in a narrow range from 20°C to 40°C. If the cell operation temperatures are too high, active materials in the cells may become thermally unstable. If the temperatures are too low, the resistance to lithium-ion transport in the cells may become very high, limiting the electrochemical reactions. Good battery thermal management is crucial to both the battery performance and life. Characteristics of various battery thermal management systems are reviewed. Analyses show that the advantages of direct and indirect air cooling systems are their simplicity and capability of cooling the cells in a battery pack at ambient temperatures up to 40°C. However, the disadvantages are their poor control of the cell-to-cell differential temperatures in the pack and their capability to dissipate high cell generations.