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Electric vehicles are receiving considerable attention because they offer a more efficient and sustainable transportation alternative compared to conventional fossil-fuel powered vehicles. Since the battery pack represents the primary energy storage component in an electric vehicle powertrain, it requires accurate monitoring and control. In order to effectively estimate the battery pack critical parameters such as the battery state of charge (SOC), state of health (SOH), and remaining capacity, a high-fidelity battery model is needed as part of a robust SOC estimation strategy. As the battery degrades, model parameters significantly change, and this model needs to account for all operating conditions throughout the battery's lifespan. For effective battery management system design, it is critical that the physical model adapts to parameter changes due to aging.

No two battery cells can be identical. Charging/discharging a battery pack without monitoring cell voltages or SoC (State-of-Charge) will cause cell voltages to deviate over time and the packs useable capacity to decrease quickly. To redistribute charge uniformly among cells, various cell balancing methods have been proposed in the literature. In this paper, a cell balancing method based on a single switched-capacitor is presented from a brand new perspective. Unlike the traditional balancing methods that rely on the voltage divergence criterion, this paper uses the SoC divergence criterion to shuttle charge from a highly charged cell to a poorly charged cell. Moreover, an equivalent resistance of the single-switched capacitor topology is derived in steady state. For fast cell balancing, design guidelines are provided for selecting a proper switching-time period and the capacitor parameters. Ultracapacitors are recommended to achieve this goal.

Due to their high energy density, power density, and durability, lithium-ion (Li-ion) batteries are rapidly becoming the most popular energy storage method for electric vehicles. Difficulty arises in accurately estimating the amount of left capacity in the battery during operation time, commonly known as battery state of charge (SOC). This paper presents a comparative study between six different Equivalent Circuit Li-ion battery models and two different state of charge (SOC) estimation strategies. The Battery models cover the state-of-the-art of Equivalent Circuit models discussed in literature. The Li-ion battery SOC is estimated using non-linear estimation strategies i.e. Extended Kalman filter (EKF) and the Smooth Variable Structure Filter (SVSF). The models and the state of charge estimation strategies are compared against simulation data obtained from AVL CRUISE software.

Hybrid, plug-in hybrid, and electric vehicles have enthusiastically embraced rechargeable Li-ion batteries as their primary/supplemental power source of choice. Because the state of charge (SoC) of a battery indicates available remaining energy, the battery management system of these vehicles must estimate the SoC accurately. To estimate the SoC of Li-ion batteries, we derive a normalized state-space model based on Li-ion electrochemistry and apply a Bayesian algorithm. The Bayesian algorithm is obtained by modifying Potter's squareroot filter and named the Potter SoC tracker (PST) in this paper. We test the PST in challenging test cases including high-rate charge/discharge cycles with outlier cell voltage measurements. The simulation results reveal that the PST can estimate the SoC with accuracy above 95% without experiencing divergence.

Advanced engine test methods incorporate several different sensing and signal processing techniques for identifying and locating manufacturing or assembly defects of an engine. A successful engine test method therefore, requires advanced signal processing techniques. This paper introduces a novel signal processing technique to successfully detect a faulty internal combustion engine in a quantitative manner. Accelerometers are mounted on the cylinder head and lug surfaces while vibration signals are recorded during engine operation. Using the engine's cam angular position, the vibration signals are transformed from the time domain to the crank-angle domain. At the heart of the transformation lies interpolation. In this paper, linear, cubic spline and sinc interpolation methods are demonstrated for reconstructing vibration signals in the crank-angle domain.

This paper describes the design of an intelligent control strategy that would allow the conversion of a gasoline engine to a bi-fuel form with minimal alteration. Conversion of a conventional gasoline engine to a bi-fuel form is easy and can be achieved at a relatively low cost. By using a bi-fuel engine in vehicles, the advantages of both natural gas and gasoline can be exploited. When the natural gas tank empties, the vehicle can be operated on gasoline until it is refueled with natural gas. This paper describes an add-on control module that is developed and applied to an engine for bi-fuel operation. The control scheme uses neural networks and is capable of substantially improving the operation of a bi-fuel engine in terms of emissions. Simulation results are reported.

It is not uncommon for complex engineering products to undergo several design iterations due to changing market expectations or inadequate performance. In such circumstances, a prototype is generally available that could be used for performance analysis before a revision to the design is made. The availability of a prototype can be an invaluable tool for the analysis of the impact of potential design changes on the system performance. In this paper, a process is proposed for the derivation of a physical model that could be used for design analysis. The process uses model identification for determination of model complexity and numerical optimization for estimation of model parameters. This process is applied to a new pneumatic fan clutch system that has been developed to improve the efficiency of engine temperature regulation in heavy-duty commercial vehicles. This system is currently in a prototype phase and its detailed physical model is required for design trade-off analysis

A hydrostatic actuation system referred to as the Electro Hydraulic Actuator (EHA) has been designed and prototyped. In this paper, a mathematical model of the EHA is reviewed and analyzed. This theoretical analysis is supported by open-loop experimental results that indicate the presence of nonlinearities but at a degree that is considerably less than that of conventional hydraulic systems with servo-valves. The behavior of the system can be approximated as piece-wise linear with the damping ratio and natural frequency changing according to a piece-wise operating region. The EHA model is used in conjunction with experimentation and numerical optimization for quantifying the influence of unknown parameters in this system. A parametric model for the EHA is subsequently proposed and validated.

This paper compares the characteristics of a high-precision hydrostatic actuator to that of conventional hydraulic systems using servovalves. Servovalve controlled hydraulic actuators retain their market share as they provide precision movement and offer a very high torque to mass ratio at the final actuation point. The input current/output torque relationship of a conventional hydraulic actuation system is reviewed in a robotic context. This relationship is summarized by a mathematical model that can be expressed in a generalized form. This model is used for the analysis of flow and dynamic characteristics. The design and modeling of a recently proposed high-performance hydrostatic actuation system referred to as the ElectroHydraulic Actuator (EHA) is briefly reviewed. A prototype of this actuator has been produced and has demonstrated a comparable performance to servovalve controlled conventional hydraulic systems.

This paper describes the design strategy adopted for developing a new high performance actuation system referred to as the ElectroHydraulic Actuator (EHA). The design approach can be divided into fives phases that include: pre-conceptual analysis, conceptual design, preliminary design, detailed design and, integration and test. An important aspect of the design process is the use of modeling and simulation for the analysis, sizing and selection of off-the-shelf parts, and for the detailed design of new custom made components. EHA is based on hydrostatic transmission. It is a unique device with its own characteristics and requires hydraulic components that are specifically tailored to its needs. A prototype of EHA has been produced and has demonstrated an extremely high level of performance. The performance of this prototype complies with design requirements and validates the chosen design approach.