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Goods movement and port related activities are a significant source of emissions in many large urban areas. Electrification of diesel cargo handling equipment is one method of reducing community exposure to these emissions, that also provides the potential for reducing greenhouse gas emissions. This study evaluated the performance of several pieces of zero emission cargo transfer equipment for a demonstration conducted at two terminal locations at the Port of Long Beach (POLB). This included the data logging of three battery-electric top handlers and one battery-electric yard tractor, as well as two baseline diesel top handlers and one diesel yard tractor. The battery-electric equipment typically operated about 5 hours per day, while using between 34 to 50% of the battery pack state of charge (SOC). In general, the battery-electric equipment was able to provide comparable hours of operation to the diesel equipment over a typical 8-hour shift.

Eco-Approach and Departure (EAD) has been considered as a promising eco-driving strategy for vehicles traveling in an urban environment, where information such as signal phase and timing (SPaT) and geometric intersection description is well utilized to guide vehicles passing through intersections in the most energy-efficient manner. Previous studies formulated the optimal trajectory planning problem as finding the shortest path on a graphical model. While this method is effective in terms of energy saving, its computation efficiency can be further enhanced by adopting machine learning techniques. In this paper, we propose an innovative deep learning-based queue-aware eco-approach and departure (DLQ-EAD) system for a plug-in hybrid electric bus (PHEB), which is able to provide an online optimal trajectory for the vehicle considering both the downstream traffic condition (i.e. traffic lights, queues) and the vehicle powertrain efficiency.

Drivers continually require steering performance improvement, particularly in the area of feedback from the road. In this study, we develop a new electrically-assisted steering logic by 1) analyzing existing steering systems to determine key factors, 2) modeling an ideal steering system from which to obtain a desirable driver torque, 3) developing a rack force observer to faithfully represent road information and 4) building a feedback compensator to track the tuned torque. In general, the estimator uses the driver torque, assist torque and other steering system signals. However, the friction of the steering system is difficult to estimate accurately. At high speed, where steering feeling is very important, greater friction results in increased error. In order to solve this problem, we design two estimators generated from a vehicle model and a steering system model. The observer that uses two estimators can reflect various operating conditions by using the strengths of each method.

Optimizing/maximizing regen braking in a hybrid electric vehicle (HEV) is one of the key features for increasing fuel economy. However, it is known [1] that maximizing regen braking by braking the rear axle on a low friction surface results in compromising vehicle stability even in a vehicle which is equipped with an ESP (Enhanced Stability Program). In this paper, we develop a strategy to maximize regen braking without compromising vehicle stability. A yaw rate stability control system is designed for a hybrid electric vehicle with electric rear axle drive (ERAD) and a “hang on” center coupling device which can couple the front and rear axles for AWD capabilities. Nonlinear models of the ERAD drivetrain and vehicle are presented using bond graphs while a high fidelity model of the center coupling device is used for simulation.

Verification and validation (V&V) are essential stages in the design cycle of industrial controllers to remove the gap between the designed and implemented controller. In this study, a model-based adaptive methodology is proposed to enable easily verifiable controller design based on the formulation of a sliding mode controller (SMC). The proposed adaptive SMC improves the controller robustness against major implementation imprecisions including sampling and quantization. The application of the proposed technique is demonstrated on the engine cold start emission control problem in a mid-size passenger car. The cold start controller is first designed in a single-input single-output (SISO) structure with three separate sliding surfaces, and then is redesigned based on a multiinput multi-output (MIMO) SMC design technique using nonlinear balanced realization.

In this paper, we propose algorithms for cost minimization of physical wires that are used to connect electronic devices in the vehicle. The wiring cost is one of the most important drivers of electrical architecture selection. Our algorithms perform wire routing from a source device to a destination device through harnesses, by selecting the optimized wire size. In addition, we provide optimized splice allocation with limited constraints. Based on the algorithms, we develop a tool which is integrated into an off-the-shelf optimization and workflow system-level design tool. The algorithms and the tool provide an efficient, flexible, scalable, and maintainable approach for cost analysis and architecture selection.

Optimizing the hardware design and control strategies of thermal management systems (TMS) in battery packs using large format pouch cells is a difficult but important problem due to the limited understanding of how internal temperature distributions impact the performance and lifetime of the pack. Understanding these impacts is difficult due to the greatly varying length and time scales between the coupled phenomena, causing the need for complex and computationally expensive models. Here, an experimental investigation is performed in which a set of fixed one-dimensional temperature distributions are applied across the face of a Nickel-Cobalt-Manganese (NCM) cathode lithium ion pouch cell in order to study the performance impacts. Effects on the open circuit voltage (OCV), Ohmic resistance, bulk discharge and charge resistance and instantaneous power are investigated.

Vehicle stability augmentation has been refined over many years, and currently there are commercial systems that control right/left braking and throttle to create vehicles that remain controlled when road conditions are very poor. These systems typically use yaw rate and lateral acceleration in their control philosophy. The tire/road friction coefficient, μ, has a significant role in vehicle longitudinal and lateral control, and there has been associated efforts to measure or estimate the road surface condition to provide additional information for the stability augmentation system. In this paper, a differential braking control strategy using yaw rate feedback, coupled with μ feedforward is introduced for a vehicle cornering on different μ roads. A nonlinear 4-wheel car model is developed. A desired yaw rate is calculated from the reference model based on the driver steering input.

This paper is written to provide information on the fuel efficiency, emissions and energy cost of vehicles ranging from a pure electric (ZEV) to gasoline hybrid vehicles with electric range varying from 30 mi (50km) to 100 mi (160km). The Federal government s PNGV and CARB s ZEV have different goals, this paper explores some possibilities for hybrid-electric vehicle designs to meet both goals with existing technologies and batteries. The SAE/CARB testing procedures for determining energy and emission performance for EV and HEV and CARB s HEV ruling for ZEV credit are also critically evaluated. This paper intends to clarify some confusion over the comparison, discussion and design of electric- hybrid- and conventional- vehicles as well.

A torque control policy for four-wheel drive road-going vehicles is developed, based on the use of a compact variable ratio unit (VRU) located at each wheel. Since the appropriate hardware is not yet available, a computer model is developed to examine what gear ratio range and frequency response might be required of the hardware to allow for improved performance and stability over current four-wheel drive systems. A comparison is then made to a front-wheel drive (FWD), rear-wheel drive (RWD) and four-wheel drive (4WD) to determine the effectiveness of the derived control policy.

The postcollision motion starts immediately upon completion of a collision impact where the vehicles obtain new sets of velocities through an exchange of momentum. Similitude with model study and fullscale automobile experiments indicate that the post-collision trajectory is essentially a plane motion, governed by inertia and tire friction. Trajectories depend on many parameters (such as tire friction coefficient, front wheel steering angle, vehicle geometrics, and whether wheels are locked or free to rotate) but not on the vehicle weight. Theoretical computation of trajectories are compared with experiments.

AN ENGINEERING evaluation of six automobile head-on collision experiments is presented for impact speeds ranging from 21 to 52 mph. An analysis of the relative collision performances of unit-body and frame-type construction is made. Anthropometric dummy subjects facilitate determination of force systems for restrained and unrestrained motorists, their dynamic and kinetic responses to impact, and the causative factors associated with motorist injury production.* The systems of instrumentation which enabled a comprehensive analysis to be made from an event lasting only 0.25 sec are briefly presented.