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This paper presents experimental investigations of diagnosing and analyzing the low-frequency, low- SNR (Signal to Noise Ratio) noise sources of three motorcycles using a hybrid technology that consists of a passive SODAR (Sonic Detection And Ranging) and modified HELS (Helmholtz Equation Least Squares) methods. The former enables one to determine the precise locations of multiple sound sources in 3D space simultaneously over the entire frequency range that is consistent with a measurement microphone in non-ideal environment, where there are random background noise and unknown interfering signals. The latter enables one to reconstruct all acoustic quantities such as the acoustic pressure, acoustic intensity, time-averaged acoustic power, radiation patterns, and sound transmission paths through arbitrarily shaped vibrating structures.

Lithium-ion polymer battery has been widely used for vehicle onboard electric energy storage ranging from 12V SLI (Starting, Lighting, and Ignition), 48V mild hybrid electric, to 300V battery electric vehicle. Formulation on cell parameters acquired from minimum numbers of experiments, the modeling and simulation could be an effective approach in predicting battery performance, thermal effectiveness, and degradation. This paper describes the modeling, simulation, and validation of Lithium-Nickel-Manganese-Cobalt-Oxide (LiNiMnCoO2) based cell with 3.6V nominal voltage and 20Ah capacity. Constant current 20A, 40A, 60A, and 80A discharge tests are conducted in the computer-controlled cycler and temperature chamber. Discharging voltage curves and cell surface temperature distributions are recorded in each discharging test. A three-dimensional cell model is constructed in the COMSOL multi-physics platform based on the cell parameters.

With the mass movement toward electrification and renewable technologies, the scope of innovation of electrification has gone beyond the automotive industry into areas such as electric motorcycle applications. This paper provides a discussion of the methodology and complexities of converting an internal combustion motorcycle to an electric motorcycle. In developing this methodology, performance goals including, speed limits, range, weight, charge times, as well as riding styles will be examined and discussed. Based on the goals of this paper, parts capable of reaching the performance targets are selected accordingly. Documentation of the build process will be presented along with the constraints, pitfalls, and difficulties associated with the process of the project. The step-by-step process that is developed can be used as a guideline for future build and should be used as necessary.

As vehicles are getting electrified and more intelligent, the energy consumption of the auxiliary system increases rapidly. The auxiliary battery acts as the backbone of the system to support the proper operation of the vehicle. It is important to ensure the auxiliary battery has enough energy to meet the basic loads regardless the vehicle is in park or running. However, the existing methods only focus on auxiliary energy management when the vehicle is in a dynamic event. To fulfill the gap, we propose an intelligent strategy that detects the low state of charge (SOC) condition, temporarily turns down the auxiliary loads based on their priorities and charges the auxiliary battery at the maximum efficiency of the auxiliary power unit. In addition, the proposed strategy allows the vehicle to get the park duration update and make intelligent decisions on charging the auxiliary battery.

This study undertakes an investigation of the effect of battery charge balance in hybrid electric vehicles (HEVs) on EPA fuel economy label values. EPA's updated method was fully implemented in 2011 and uses equations which weight the contributions of fuel consumption results from multiple dynamometer tests to synthesize city and highway estimates that reflect average U.S. driving patterns. For the US06 and UDDS cycles, the test results used in the computation come from individual phases within the overall certification driving cycles. This methodology causes additional complexities for hybrid vehicles, because although they are required to be charge-balanced over the course of a full drive cycle, they may have net charge or discharge within the individual phases. As a result, the fuel consumption value used in the label value calculation can be skewed.

The objective of this work is to provide a relatively simple battery energy storage and loss model that can be used for technology screening and design/sizing studies of hybrid electric vehicle powertrains. The model dynamic input requires only power demand from the battery terminals (either charging or discharging), and outputs internal battery losses, state-of-charge (SOC), and pack temperature. Measured data from a vehicle validates the model, which achieves reasonable accuracy for current levels up to 100 amps for the size battery tested. At higher current levels, the model tends to report a higher current than what is needed to create the same power level shown through the measured data. Therefore, this battery model is suitable for evaluating hybrid vehicle technology and energy use for part load drive cycles.

This paper covers the development of a closed loop transaxle synchronization algorithm which was a key deliverable in the control system design for the L3 Enigma, a Battery Dominant Hybrid Electric Vehicle. Background information is provided to help the reader understand the history that lead to this unique solution of the input and output shaft synchronizing that typically takes place in a manual vehicle transmission or transaxle when shifting into a gear from another or into a gear from neutral when at speed. The algorithm stability is discussed as it applies to system stability and how stability impacts the speed at which a shift can take place. Results are simulated in The MathWorks Simulink programming environment and show how traction motor technology can be used to efficiently solve what is often a machine design issue. The vehicle test bed to which this research is applied is a parallel biodiesel hybrid electric vehicle called the Enigma.

An automotive powertrain system consists of several interactive and linked nonlinear systems. This research focuses on the coordination of Gasoline Direct Injection (GDI) engine, transmission and emission aftertreatment systems. The goal is to design an optimal control strategy for driving performance, emissions (HC, CO, NOX), fuel economy and smoothness when switching engine mode and when shifting gears, under both discrete and continuous limitations. A multivariable control strategy is used to compromise among all powertrain subsystems to achieve optimal overall performance. A nonlinear discrete dynamic programming approach is proposed for hybrid system optimization. The complex multivariable automotive control problem is then simplified into an optimization problem. The feasibility of automotive hybrid control via the discrete dynamic programming approach is demonstrated by results from many numerical simulations under different operating conditions.

Modern fatigue analysis techniques, that can provide reliable estimates of the service performance of components and structures, are finding increasing use in vehicle development programs. A major objective of such efforts is the prediction of the field performance of a fleet of vehicles as influenced by the host of design, manufacturing, and performance variables. An approach to this complex problem, based on the incorporation of probability theory in established life prediction methods, is presented. In this way, quantitative estimates of the lifetime distribution of a population are obtained based on anticipated, or specified, variations in component geometry, material processing sequences, and service loading. The application of this approach is demonstrated through a case study of an automotive transmission component.

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is currently developing a control strategy for a parallel plug-in hybrid electric vehicle (PHEV). The hybrid powertrain is being implemented in a 2016 Chevrolet Camaro for the EcoCAR 3 competition. Fuzzy rule sets determine the torque split between the motor and the engine using the accelerator pedal position, vehicle speed and state of charge (SOC) as the input variables. The torque producing components are a 280 kW V8 L83 engine with active fuel management (AFM) and a post-transmission (P3) 100 kW custom motor. The vehicle operates in charge depleting (CD) and charge sustaining (CS) modes. In CD mode, the model drives as an electric vehicle (EV) and depletes the battery pack till a lower state of charge threshold is reached. Then CS operation begins, and driver demand is supplied by the engine operating in V8 or AFM modes with supplemental or loading torque from the P3 motor.

This paper details the development of the control algorithms to characterize the behavior of an electrohydraulic actuated dry clutch used in the powertrain of the Wayne State University EcoCAR 3 Pre-Transmission Parallel hybrid vehicle. The paper describes the methodology and processes behind the development of the clutch physical model and electronic control unit to support the calibration of the vehicle’s hybrid supervisory controller. The EcoCAR 3 competition challenges sixteen North American universities to re-engineer the 2016 Chevrolet Camaro to reduce its environmental impact without compromising its performance and consumer acceptability. The team is in final stages of Year Two competition, which focuses on the powertrain components integration into the selected hybrid architecture. The dry clutch used by the team to enable the coupling between the engine and the electric motor is a key component of the Pre-Transmission Parallel configuration.

This paper details the development of a test-bench simulation to characterize the behavior of an electro-hydraulic actuated dry clutch used in a pre-transmission parallel hybrid powertrain architecture of Wayne State University EcoCAR 3. Engage and disengage systems play a crucial role in a pre-transmission parallel hybrid architecture. The most common device used to meet the purpose of physically connecting internal combustion engine and electric powertrains is a dry clutch. Its own characteristics and capabilities allow its usage for this application. The transition between the pure electric and hybrid modes is dictated by the main control strategy. Therefore, the engaging system will be widely used when switching from charge depleting to charge sustaining mode, and vice versa. In addition, when torque is required from both sources for higher performance, the clutch will be responsible for mechanically connecting both torque sources.

The objective of the research into modeling and simulation was to provide an improvement to the Wayne State EcoCAR 2 team’s math-based modeling and simulation tools for hybrid electric vehicle powertrain analysis, with a goal of improving the simulation results to be less than 10% error to experimental data. The team used the modeling and simulation tools for evaluating different outcomes based on hybrid powertrain architecture changes (hardware), and controls code development and testing (software). The first step was model validation to experimental data, as the plant models had not yet been validated. This paper includes the results of the team’s work in the U.S. Department of Energy’s EcoCAR 2 Advanced vehicle Technical Competition for university student teams to create and test a plug-in hybrid electric vehicle for reducing petroleum oil consumption, pollutant emissions, and Green House Gas (GHG) emissions.

In this work, a pseudo three-dimensional coupled thermal-electrochemical model is established to estimate the heat generation and temperature profiles of a lithium ion battery as functions of the state of the discharge. Then, this model is used to investigate the effectiveness of active and passive thermal management systems. The active cooling system utilizes cooling plate and water as the working fluid while the passive cooling system incorporates a phase change material (PCM). The thermal effects of coolant flow rate examined using a computational fluid dynamics model. In the passive cooling system, Paraffin wax used as a heat dissipation source to control battery temperature rise. The effect of module size and battery spacing is studied to find the optimal weight of PCM required. The results show that although the active cooling system has the capability to reduce the peak temperatures, it leads to a large temperature difference over the battery module.

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2009 - 2011 EcoCAR: The NeXt Challenge Advanced Vehicle Technology Competition series organized by Argonne National Lab (ANL), and sponsored by General Motors Corporation (GM), and the U.S. Department of Energy (DOE). Following GM's Vehicle Development Process (VDP), HEVT established team goals that meet or exceed the competition requirements for EcoCAR in the design of a plug-in extended-range hybrid electric vehicle. The competition requires participating teams to improve and redesign a stock Vue XE donated by GM. The result of this design process is an Extended-Range Electric Vehicle (E-REV) that uses grid electric energy and E85 fuel for propulsion. The vehicle design is predicted to achieve an SAE J1711 utility factor corrected fuel consumption of 2.9 L(ge)/100 km (82 mpgge) with an estimated all electric range of 69 km (43 miles) [1].

The Wayne State University (WSU) EcoCAR 2 Team designed the conversion of a GM donated 2013 Chevrolet Malibu to a Parallel-Through-The-Road (PTTR) Plug-In Hybrid vehicle within a 9 month timeframe. This fast prototyping project used the EcoCAR 2 Vehicle Development Process (EVDP). Various tradeoffs were made to meet all competition requirements and to make the vehicle as competitive as possible within budget, time and experience limitations. The chosen PTTR architecture, nicknamed by the team as “E2D2” (Ethanol-Electric Dual-Drivetrain), provides up to 35.7 electric only miles and a fuel economy of 60 miles per gallons gasoline equivalent (mpgge) or 3.96 liters gasoline equivalent (lge) per one hundred km. This is accomplished using an E85 engine-driven front traction system and a battery-electric-motors-driven rear traction system. The team developed the control system and designed the packaging and integration of all required components including the Energy Storage System (ESS).

The Hybrid Electric Vehicle Team (HEVT) of Virginia Tech has achieved the Year 2 goal of producing a 65% functional mule vehicle suitable for testing and refinement, while maintaining the series-parallel plug-in hybrid architecture developed during Year 1. Even so, further design and expert consultations necessitated an extensive redesign of the rear powertrain and front auxiliary systems packaging. The revised rear powertrain consists of the planned Rear Traction Motor (RTM), coupled to a single-speed transmission. New information, such as the dimensions of the high voltage (HV) air conditioning compressor and the P2 motor inverter, required the repackaging of the hybrid components in the engine bay. The P2 motor/generator was incorporated into the vehicle after spreading the engine and transmission to allow for the required space.

The central performance requirement for electrochemical energy storage systems for the full power-assist hybrid electric vehicle (HEV) is pulse power capability, typically 25-40 kW pulse power capability for 10 seconds duration. Standard test procedures utilize constant current pulses. However, in the HEV application, the power transient for acceleration is a ramped power transient and the power transient for regenerative braking power is a descending power ramp. This paper compares the usable power capability of batteries and supercapacitors under constant current, constant power, and ramped power transients. Although the usable battery discharge power is relatively insensitive to the transient type applied, 10-40% higher regenerative braking charge capability is observed with ramped power transients. With supercapacitors, the discharge and charge capability is much more strongly dependent on the type of power transient.

The Wayne State University (WSU) EcoCAR2 student team designed, modeled, Model-In-the-Loop (MIL) tested, Software-In-the-Loop (SIL) simulation tested, and Hardware-In-the-Loop (HIL) simulation tested the team's conversion design for taking a 2013 Chevrolet Malibu and converting it into a Parallel-Through-The-Road (PTTR) plug-in hybrid. The 2013 Malibu is a conventional Front Wheel Drive (FWD) vehicle and the team's conversion design keeps the conventional FWD and adds a Rear Wheel Drive (RWD) powertrain consisting of an electric motor, a single speed reduction gearbox and a differential to drive the rear wheels -where none of these previously existed on the rear wheels. The RWD addition creates the PTTR hybrid powertrain architecture of two driven axles where the mechanical torque path connection between the two powertrains is through the road, rather than a mechanical torque path through gears, chains, or shafts.

The pre-prototype development of a simulated rule-based hybrid energy management strategy for a 2019 Chevrolet Blazer RS converted parallel P4 full hybrid is presented. A vehicle simulation model is developed using component bench data and validated using EPA-reported dynamometer fuel economy test data. A combined Willans line model is proposed for the engine and transmission, with hybrid control rules based on efficiency-derived engine power thresholds. Algorithms are proposed for battery state of charge (SOC) management including engine loading and one pedal strategies, with battery SOC maintained within 20% to 80% safe limits and charge balanced behavior achieved. The simulated rule-based hybrid control strategy for the hybrid vehicle has an energy consumption reduction of 20% for the Hot 505, 3.6% for the HwFET, and 12% for the US06 compared to the stock vehicle.