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Battery temperature variations have a strong effect on both battery aging and battery performance. Significant temperature variations will lead to different battery behaviors. This influences the performance of the Hybrid Electric Vehicle (HEV) energy management strategies. This paper investigates how variations in battery temperature will affect Lithium-ion battery aging and fuel economy of a HEV. The investigated energy management strategy used in this paper is the Equivalent Consumption Minimization Strategy (ECMS) which is a well-known energy management strategy for HEVs. The studied vehicle is a Honda Civic Hybrid and the studied battery, a BLS LiFePO4 3.2Volts 100Ah Electric Vehicle battery cell. Vehicle simulations were done with a validated vehicle model using multiple combinations of highway and city drive cycles. The battery temperature variation is studied with regards to outside air temperature.

Advanced internal combustion engines, although generally more efficient than conventional combustion engines, often encounter limitations in multi-cylinder applications due to variations in the combustion process. This study leverages experimental data from an inline 6-cylinder heavy-duty dual fuel engine equipped with a fully-flexible variable intake valve actuation system to study cylinder-to-cylinder variations in power production. The engine is operated with late intake valve closure timings in a dual-fuel combustion mode featuring a port-injection and a direct-injection fueling system in order to improve fuel efficiency and engine performance. Experimental results show increased cylinder-to-cylinder variation in IMEP as IVC timing moves from 570°ATDC to 610°ATDC, indicating an increasingly uneven fuel distribution between cylinders.

Low Temperature Combustion (LTC) engines are promising to improve powertrain fuel economy and reduce NOx and soot emissions by improving the in-cylinder combustion process. However, the narrow operating range of LTC engines limits the use of these engines in conventional powertrains. The engine’s limited operating range can be improved by taking advantage of electrification in the powertrain. In this study, a multi-mode LTC-SI engine is integrated with a parallel hybrid electric configuration, where the engine operation modes include Homogeneous Charge Compression Ignition (HCCI), Reactivity Controlled Compression Ignition (RCCI), and conventional Spark Ignition (SI). The powertrain controller is designed to enable switching among different modes, with minimum fuel penalty for transient engine operations.

Software systems on electronically controlled diesel truck engines typically provide diagnostic features to enable the engine mechanic to identify and debug system problems. As future systems become more sophisticated, so will the diagnostic requirements. The advantages of serviceability and accuracy found in todays electronic systems must not be allowed to degrade due to this increased sophistication. One method of maintaining a high level of serviceability and accuracy is to place an even greater priority on diagnostics and servicing in the initial design phase of the product than is done today. In particular, three major goals of future diagnostic systems should be separation of component failures from system failures, prognostication of failures and analysis of engine performance. This paper will discuss a system to realize these goals by dividing the diagnostic task into the Electronic System Diagnostics, Engine System Diagnostics and the Diagnostic Interface.

This paper presents an overview of the connected controls and optimization system for vehicle dynamics and powertrain operation on a light-duty plug-in multi-mode hybrid electric vehicle developed as part of the DOE ARPA-E NEXTCAR program by Michigan Technological University in partnership with General Motors Co. The objective is to enable a 20% reduction in overall energy consumption and a 6% increase in electric vehicle range of a plug-in hybrid electric vehicle through the utilization of connected and automated vehicle technologies. Technologies developed to achieve this goal were developed in two categories, the vehicle control level and the powertrain control level. Tools at the vehicle control level include Eco Routing, Speed Harmonization, Eco Approach and Departure and in-situ vehicle parameter characterization.

The Kalman and Vold-Kalman order tracking filters have been implemented in commercial software since the early 90's. There are several mathematical formulations of filters that have been implemented by different software vendors. However, there have not been any papers that have been published which sufficiently explain the math behind these filters and discuss the actual implementations of the filters in software. In addition, upon generating the equations represented by these filters, solving the equations for datasets in excess of several hundred thousand datapoints is not trivial and has not been discussed in the literature. The papers which have attempted to cover these topics are generally vague and overly mathematically eloquent but not easily understandable by a practicing engineer.

Fuel is a significant portion of the operating cost for an on-highway diesel engine and fuel economy is important to the economics of shipping most goods in North America. Cat® ACERT™ engine technology is no exception. Ball bearings have been applied to the series turbochargers for the Caterpillar heavy-duty, on-highway diesel truck engines in order to reduce mechanical loss for improved efficiency and lower fuel consumption. Over many years of turbocharger development, much effort has been put into improving the aerodynamic efficiency of the compressor and turbine stages. Over the same span of time, the mechanical bearing losses of a turbocharger have not experienced a significant reduction in power consumption. Most turbochargers continue to use conventional hydrodynamic radial and thrust bearings to support the rotor. While these conventional bearings provide a low cost solution, they do create significant mechanical loss.

The Time Variant Discrete Fourier Transform was implemented as a real-time order tracking method using developed software and commercially available hardware. The time variant discrete Fourier transform (TVDFT) with the application of the orthogonality compensation matrix allows multiple tachometers to be tracked with close and/or crossing orders to be separated in real-time. Signal generators were used to create controlled experimental data sets to simulate tachometers and response channels. Computation timing was evaluated for the data collection procedure and each of the data processing steps to determine how each part of the process affects overall performance. Many difficulties are associated with a real-time data collection and analysis tool and it becomes apparent that an understanding of each component in the system is required to determine where time consuming computation is located.

Safety control and protection strategy of high-voltage system of electric vehicles include analysis of circuit condition before connection to high voltage terminal, transient current prevention for capacitive load, real-time monitoring and analysis of high-voltage system during operation, disconnecting strategy of high voltage terminals, vehicle dynamic safety and cooperative management of electrical systems, etc. Monitoring and analysis of some critical parameters of high voltage system such as insulation, electrical harness and connector condition are the basis and difficulties in high-voltage safety and protection. This paper presents several mathematical models of monitoring critical parameters, and experiments were also done to evaluate the model. Disadvantages of the commonly used calculation method are discussed. Single point insulation defect model is introduced and diagnosis method of multiple points defect is also discussed.

Optimal fuel injection strategies are obtained with a micro-genetic algorithm and an adaptive gradient method for a nonroad, medium-speed DI diesel engine equipped with a multi-orifice, asynchronous fuel injection system. The gradient optimization utilizes a fast-converging backtracking algorithm and an adaptive cost function which is based on the penalty method, where the penalty coefficient is increased after every line search. The micro-genetic algorithm uses parameter combinations of the best two individuals in each generation until a local convergence is achieved, and then generates a random population to continue the global search. The optimizations have been performed for a two pulse fuel injection strategy where the optimization parameters are the injection timings and the nozzle orifice diameters.

This paper introduces design, control, and power management of a battery/ ultra-capacitor hybrid system, utilized for small electric vehicles (EV). The batteries are designed and controlled to work as the main energy storage source of the vehicle, supplying average power to the load; and the ultra-capacitors are used to meet the peak power demands during transients. Power management system determines the directions of power flow, according to load demand. Presented analyses validate the efficient power management methodology.

A cooperative program between the DOE Office of Heavy Vehicle Technology and Caterpillar is aimed at demonstrating electric turbo compound technology on a Class 8 truck engine. The goal is to demonstrate the level of fuel efficiency improvement attainable with an electric turbocompound system. The system consists of a turbocharger with an electric motor/generator integrated into the turbo shaft. The generator extracts surplus power at the turbine, and the electricity it produces is used to run a motor mounted on the engine crankshaft, recovering otherwise wasted energy in the exhaust gases. The electric turbocompound system also provides more control flexibility in that the amount of power extracted can be varied. This allows for control of engine boost and thus air/fuel ratio. The paper presents the status of development of an electric turbocompound system for a Caterpillar heavy-duty on-highway truck engine.

This paper analyzes the control of the series-parallel powersplit used in the 2001 Michigan Tech FutureTruck. An electronic throttle controller is implemented and a new control algorithm is proposed and tested. A vehicle simulation has been created in MATLAB and the control algorithm implemented within the simulation. A program written in C has also been created that implements the control algorithm in the test vehicle. The results from both the simulation and test vehicle are presented and discussed and show a 15% increase in fuel economy. With the increase in fuel economy, and through the use of the original exhaust after treatment, lower emissions are also expected.

Demands for higher fuel economy, performance, reliability, convenience, as well as reduced emissions push the automotive industry to seek electrification of ancillaries and engine augmentations. In cars of the future, throttle actuation, steering, anti-lock braking, rear-wheel steering, active suspension and ride-height adjustment, air-conditioning, and electrically heated catalyst will all benefit from the electrical power system. Therefore, a higher system voltage, such as the proposed 42V, is necessary to handle these new introduced loads. In this paper, an overview of the systems that will benefit from the 42V bus is presented. Effects of the new introduced electrical loads on the electrical power systems of conventional cars are described. Dynamic characteristics of each load for a typical drive cycle are defined. In addition, system level issues and vehicle performances such as fuel economy are addressed.

With the increase of hotel and ancillary loads and replacement of engine driven mechanical and hydraulic loads with electrical loads, automotive systems are becoming more electric. This is the concept of More Electric Cars (MEC) that necessitates a higher system voltage, such as the proposed 42V, for conventional cars. In this paper, the development of the 42V electric power system for vehicle applications is reviewed. The system architecture and motor drive problems associated with the 42V electric power system are analyzed. Solutions to these problems are also discussed.

In this paper, the conversion of a production sport utility vehicle (SUV) to a hybrid electric vehicle utilizing a through-the-road parallel hybrid configuration is presented. The uniqueness of this design comes from its ability to decouple the front and rear drivetrain to simplify the packaging of underbody components. The Hybrid Theory utilizes a 2.0L, 4-cylinder engine that supplies 101kW (135hp) to the front wheels and a DC motor that supplies an additional 53kW (70hp) to the rear wheels to achieve the competition goals of a 25% improvement in fuel economy, a reduction in Green House Gas (GHG) emissions, as well as maintaining stock performance. The effects on drivability, manufacturing, fuel economy, emissions, and performance are presented along with the design, selection, and implementation of all of the vehicle conversion components.

In order to improve efficiency and increase the operation of electric vehicles, assistive energy regeneration systems can be used. A hydraulic energy recovery system is modeled to be used as a regenerative system for supplementing energy storage for a pure electric articulated passenger bus. In this study a pump/motor machine is modeled to transform kinetic energy into hydraulic energy during braking, to move the hydraulic fluid from the low pressure reservoir to the hydraulic accumulator. The simulation of the proposed system was used to estimate battery savings. It was found that on average, approximately 39% of the battery charge can be saved when using a real bus driving cycle.

China has become the world’s largest vehicle market in terms of sales volume. Automobiles sales keep growing in recent years despite the declining economic growth rate. Due to the increasing attention given to the environmental impact, more stringent emission regulations are being drafted to control traditional internal combustion engine emissions. In order to reduce vehicle emissions, environmentally-friendly new-energy vehicles, such as electric vehicles and plug-in hybrid vehicles, are being promoted by government policies. The Chinese government plans to boost sales of new-energy cars to account for about five percent of China’s total vehicle sales. It is well known that more electric and electronic components will be integrated into a vehicle platform during vehicle electrification.

The increased market share of electric vehicles and renewable energy resources have raised concerns about their impact on the current electrical distribution grid. To achieve sustainable and stable power distribution, a lot of effort has been made to implement smart grids. This paper addresses Demand Response (DR) load control in a smart grid using Internet of Things (IoT) technology. A smart grid is a networked electrical grid which includes a variety of components and sub-systems, including renewable energy resources, controllable loads, smart meters, and automation devices. An IoT approach is a good fit for the control and energy management of smart grids. Although there are various commercial systems available for smart grid control, the systems based on open sources are limited. In this study, we adopt an open source development platform named Node-RED to integrate DR capabilities in a smart grid for DR load control. The DR system employs the OpenADR standard.

Vehicle-to-Grid (V2G) service has a potential to improve the reliability and stability of the electrical grid due to the ability of providing bi-directional power flow from/to the grid. However, frequent charging/discharging may impact the battery lifetime. This paper presents the analysis of battery degradation in three scenarios. In the first scenario, different battery capacities are considered. In the second scenario, the battery degradation with various depth of discharge (DOD) are studied. In the third scenario, the capacity loss due to different charging regime are compared. The charging/discharging of plug-in electric vehicles (PEVs) are simulated in a single-phase microgrid system integrated with a photovoltaics (PV) farm, an energy storage system (ESS), and ten electric vehicle service equipment (EVSE). The battery degradation model is an energy throughput model, which is developed based on the Arrhenius equation and a power law relationship between time and capacity fading.