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A large amount of heat is generated in electric vehicle battery packs during high rate charging, resulting in the need for effective cooling methods. In this paper, a prototype liquid cooled large format Lithium-ion battery module is modeled and tested. Experiments are conducted on the module, which includes 31Ah NMC/Graphite pouch battery cells sandwiched by a foam thermal pad and heat sinks on both sides. The module is instrumented with twenty T-type thermocouples to measure thermal characteristics including the cell and foam surface temperature, heat flux distribution, and the heat generation from batteries under up to 5C rate ultra-fast charging. Constant power loss tests are also performed in which battery loss can be directly measured.

In this paper, a comparison between different six-phase machine topologies is conducted considering their technical performance for automotive applications. Asymmetrical and symmetrical configurations, as well as neutral point connection, are considered as candidate topologies and modelled using vector space decomposition (VSD) and double stator or double dq transformations. In both cases, a generalized model to include an arbitrary phase shift between the windings is presented as well as the effect of the neutral connection on the inverter model. For the selection, the steady-state and post-fault performance are considered in terms of control flexibility, fault-tolerant capability, and dc-link voltage utilization. For the latest, the different topologies are evaluated operating in both linear and overmodulation regions based on space vector modulation (SVM).

The Model-Based Development (MBD) paradigm is widely used for embedded controls development, with the MathWorks Simulink modelling environment being extensively used in the automotive industry. As production-scale Simulink models are typically large and complex, there exists a need to decompose them properly in order to facilitate their maintainability, understandability, and evolution. MathWorks recommends the use of three constructs for model “componentization” or decomposition: the Subsystem, Library, and Model Reference. However, a recently added construct introduced in Simulink R2014b, the Simulink Function, can also be used for this purpose, while also supporting information hiding due to the construct’s ability to be scoped and encapsulate data.

This paper proposes a domain-centralized powertrain E/E (electrical and/or electronic) architecture for all-electric vehicles that features: a powerful master controller (domain controller) that implements most of the functionality of the domain; a set of smart actuators for electric motor(s), HV (High Voltage) battery pack, and thermal management; and a gateway that routes all hardware signals, including digital and analog I/O, and field bus signals between the domain controller and the rest of the vehicle that is outside of the domain. Major functional safety aspects of the architecture are presented and a safety architecture is proposed. The work represents an early E/E architecture proposal. In particular, detailed partitioning of software components over the domain’s Electronic Control Units (ECUs) has not been determined yet; instead, potential partitioning schemes are discussed.

The assessment and control of driveline dynamics is only possible if a representative model is available. A driveline model enables engineers to estimate the system’s reactions for different torque inputs and shows how those inputs impact drivability and comfort. Modelling methods in literature are frequently designed only for internal combustion engine vehicles, disregarding electrified powertrains. To remedy that, a modelling method for electrified drivelines is presented. It simplifies the inclusion of dynamic factors such as road resistances, flexibility, friction, and inertias. The method consists in drawing a vertical diagram of the drivetrain topology where each key component is represented as a block. Newton’s second law is used to balance torque in each block connection, from propelling systems to the wheels. State variables and inputs are defined accounting for the powertrain topology.

This paper presents the characteristics of more than 260 trim levels for over 50 production electric vehicle (EV) models on the market since 2014. Data analysis shows a clear trend of all-wheel-drive (AWD) powertrains being increasingly offered on the market from original equipment manufacturers (OEMs). The latest data from the U.S. Environmental Protection Agency (EPA) shows that AWD EVs have seen a nearly 4 times increase in production from 21 models in 2020 to 79 models in 2023. Meanwhile single axle front-wheel-drive (FWD) and rear-wheel-drive (RWD) drivetrains have seen small to moderate increases over the same period, going from 9 to 11 models and from 5 to 12 models, respectively. Further looking into AWD architectures demonstrates dual electric machine (EM) powertrains using different EM types on each axle remain a small portion of the dual-motor AWD category.

Component sizing generally represents a demanding and time-consuming task in the development process of electrified powertrains. A couple of processes are available in literature for sizing the hybrid electric vehicle (HEV) components. These processes employ either time-consuming global optimization techniques like dynamic programming (DP) or near-optimal techniques that require iterative and uncertain tuning of evaluation parameters like the Pontryagin’s minimum principle (PMP). Recently, a novel near-optimal technique has been devised for rapidly predicting the optimal fuel economy benchmark of design options for electrified powertrains. This method, named slope-weighted energy-based rapid control analysis (SERCA), has been demonstrated producing results comparable to DP, while limiting the associated computational time by near two orders of magnitude.

Meticulous design of the energy management control algorithm is required to exploit all fuel-saving potentials of a hybrid electric vehicle. Equivalent consumption minimization strategy is a well-known representative of on-line strategies that can give near-optimal solutions without knowing the future driving tasks. In this context, this paper aims to propose an adaptive real-time equivalent consumption minimization strategy for a multi-mode hybrid electric powertrain. With the help of road recognition and vehicle speed prediction techniques, future driving conditions can be predicted over a certain horizon. Based on the predicted power demand, the optimal equivalence factor is calculated in advance by using bisection method and implemented for the upcoming driving period. In such a way, the equivalence factor is updated periodically to achieve charge sustaining operation and optimality.

Dual three-phase (DTP) permanent magnet synchronous machines (PMSMs) are becoming attractive for electric vehicle (EV) propulsion systems in the automotive industry. Flux-weakening (FW) control technique is important to ensure DTP-PMSMs operating in high-speed range. This paper proposes an adaptive FW control algorithm to ensure better performance and stability in variant speeds. A small-signal model is developed to obtain the adaptive gain for a constant controller bandwidth regardless of the speeds. The proposed FW controller is implemented, tuned, and validated on a DTP-PMSM experiment setup. The proposed method improves the FW performances in terms of torque and system stability, compared with the non-adaptive FW controller. Moreover, the harmonics analysis shows an inevitable xy-components affecting the overall performances. The effect of xy controller gain is further investigated for the FW operation.

To comply with the stringent fuel consumption requirements, many automobile manufacturers have launched vehicle electrification programs which are representing a paradigm shift in vehicle design. Looking specifically at powertrain calibration, optimization approaches were developed to help the decision-making process in the powertrain control. Due to computational power limitations the most common approach is still the use of powertrain calibration tables in a rule-based controller. This is true despite the fact that the most common manual tuning can be quite long and exhausting, and with the optimal consumption behavior rarely being achieved. The present work proposes a simulation tool that has the objective to automate the process of tuning a calibration table in a powertrain model. To achieve that, it is first necessary to define the optimal reference performance.

Modern powertrains are highly complex systems whose development requires careful tuning of hundreds of parameters, called calibrations. These calibrations determine essential vehicle attributes such as performance, dynamics, fuel consumption, emissions, noise, vibrations, harshness, etc. This paper presents a methodology for automatic generation of calibrations for a powertrain-abstraction software module within the powertrain software of hybrid electric vehicles. This module hides the underlying powertrain architecture from the remaining powertrain software. The module encodes the powertrain’s torque-speed equations as calibrations. The methodology commences with modeling the powertrain in MapleSim, a multi-domain modeling and simulation tool. Then, the underlying mathematical representation of the modeled powertrain is generated from the MapleSim model using Maple, MapleSim’s symbolic engine.

The purpose of this study was to conduct a comparative corrosion assessment of alloys and coating schemes of interest for the fabrication of multi-material lightweight vehicle architectures. Alloys considered for this application included galvanized high strength low alloy steel, aluminum alloy AA6111 and magnesium alloy ZEK100. The coating scheme considered for corrosion protection included a layered paint top-coat scheme that was applied to a pre-treated surface. The pre-treatments included an alloy-specific commercial conversion coating (CC) and a plasma electrolytic deposition (PED) process that was applied only to the ZEK100 material. The corrosion assessment of the scribed coated alloy panels was conducted after 1000 h exposure in the ASTM B117 salt fog environment. Characterization of the mode and extent of corrosion damage observed and the role played by the exposed alloy microstructure utilized both light optical microscopy and electron microscopy.

The purpose of this work was to initiate a comparative evaluation of the aqueous corrosion resistance of ferritic stainless steels currently used to fabricate automotive exhaust systems. Both acid condensate and double loop electrochemical potentiokinetic reactivation (DL-EPR) testing using both as-received and heat treated test coupons prepared from Types 409, 409Al, 436 and 439 stainless steel was conducted for this purpose. A truncated version of an in-house acid condensate testing protocol revealed that Type 409Al stainless steel was the most resistant to corrosion of the four ferritic stainless steels examined, whereas Type 409 stainless steel was the least resistance to corrosion.

Using standard tensile testing methods, the material properties of AKDQ and DP600 steels tubes along the axial direction were determined. A novel in-situ optical strain mapping system ARAMIS® was utilized to evaluate the strain distribution during tensile testing along the axial direction. Microstructural and damage characterization was carried out using microscopy and image analysis techniques to compare the damage evolution and formability of both materials. Failure in both steels was observed to occur via a ductile failure mode. AKDQ was found to be the more formable material as it can achieve higher strains, total elongations and thinning prior to failure than the higher strength DP600.

Using urea-based Selected Catalytic Reduction (SCR) systems is an effective way in diesel engine after-treatment systems to meet increasingly stringent emission regulations. The amount of urea injection is critical to achieve high NOx reduction efficiency and low ammonia slip and overdosing or under-dosing of urea injection need to be avoided. One of the difficulties in urea injection amount control lies in the accurate measurement/estimation of the urea injection mass. To effectively address this issue, this paper defined a correction factor for under-dosing or overdosing detection and correction and proposed two methods to identify the correction factor. The first method is based on urea pump model and line pressure. Through frequency analysis, the relation between the urea pump speed and power spectrum characteristics of the line pressure by using FFT method was revealed.

This paper presents a Differential Flatness-Based Control (FBC) approach for the current control of Switched Reluctance Machines (SRMs), a potential candidate for the automotive industry. The main challenges in SRM control methods stem from motor nonlinearity. In electrical drives, FBC has been applied in doubly-fed induction generators, permanent magnet motors, and magnet-assisted synchronous reluctance motors. Among the few papers that have used FBC for SRM, this research distinguishes itself by addressing current control and considering both current and flux-linkage separately as a flat output, an approach not found in previous literature. The performance of the proposed controls is assessed in a three-phase 12/8 SRM against the conventional hysteresis current controller (HCC) and PI controller. Additionally, it is integrated into a torque-sharing function based on a maximum torque per ampere control strategy.

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.

The application of high strength steels in tube hydroforming is being considered as one of the most effective ways to achieve the overall weight reduction without compromising the vehicle safety (crashworthiness). In this paper, the tensile behaviour of high strength dual-phase steel DP600 was investigated. The microstructure, mechanical performance and damage evolution was evaluated. A new finite element (FE) model based on crystal plasticity theory was developed to investigate large strain phenomena in multi-phase materials.

We have studied the formability of continuous strip cast (CC) AA5754 aluminum alloy for automotive applications. Strip casting technology can considerably reduce material cost compared with conventional direct chill (DC) cast aluminum sheets. However, the CC material tends to exhibit much less post-localization deformation and lower fracture strains compared with DC sheets with similar Fe content, although both alloys show similar strains for the onset of localization. Bendability of the CC alloy is also found to be inferior. The inferior behavior (post-necking and bendability) of the CC alloy can be attributed to the higher incidence of stringer-type particle distributions in the alloy. The formability of the AA5754 alloy has also been studied using two dimensional microstructure-based finite element modeling. The microstructures are represented by grains and experimentally measured particle distributions.

In recent years, environmental regulations in the automotive industry have become increasingly strict, particularly with respect to emissions from diesel engines. Large amounts of these harmful emissions are released during the cfold start of a vehicle, due to the catalytic converter system not yet reaching its light-off temperature. This paper presents an induction heating system which heats the catalytic converter during a cold start, reducing the time for it to reach light-off temperature, and thus reducing cold-start emissions. Detailed dynamometer testing results are used to develop vehicle models of the induction heating system for a diesel Peugeot 308 light duty vehicle. The model is used to quantify the changes in hydrocarbons (HC), carbon monoxide (CO), carbon dioxide (CO2), oxygen (O2), nitrogen oxide (NOx), and fuel consumption on a variety of standard drive cycles.