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The purpose of this study is to propose an extended reliability method for an industrial motor drive by integrating the physics of failure (PoF).

Industrial motor drive systems (IMDS) are currently expected to perform beyond the desired operating conditions to meet the demand. The PoF of the subsystem affects its reliability under such harsh operating circumstances. It is crucial to estimate reliability by integrating PoF, which helps in understanding its impact and to develop a fault-tolerant design, particularly in such an integrated drive system. An integrated PoF extended reliability method for industrial drive system is proposed to address this issue. In research, the numerical failure rate of each component of industrial drive is obtained first with the help of the MIL-HDBK-217 military handbook. Furthermore, the mathematically deduced proposed approach is modeled in the GoldSim Monte Carlo reliability workbench.

From the results, for a 15% rise in integrated PoF, the reliability and availability of the entire IMDS dropped by 23%, resulting in an impact on mean time to failure (MTTF).

The integrated PoF of the motor and motor controller affects industrial drive reliability, which falls to 0.18 with the least MTTF (2.27 years); whose overall reliability of industrial drive drops to 0.06 if it is additionally integrated with communication protocol.

The purpose of this study is to analyze direct current (DC) drive stability, including parameter uncertainty and perturbation in the feedback loop, by computing disk margins.

Although the closed-loop stability analysis of a DC drive has been presented well in the referenced papers, the effect of parameter uncertainty and perturbation in the feedback loop has not yet been discussed well. In this study, the conventional and disk-based stability margins were measured and compared for the nominal parameters of the DC drive. Subsequently, the smallest disk-based margins that destabilize the feedback loop for a given perturbation are computed and compared with normal disk margins.

The disk-based margin offered by the DC drive controlled by the JAYA-PID controller is disk gain margins (DGM) = 8.41 dB and disk phase margin (DPM) = 48.410 and the smallest disk-based margin offered is DGM = 1.51 dB and DPM = 9.950. In addition, the effect of the modeled uncertainty on the disk stability margins was analyzed, and it was observed that the maximum allowable parameter uncertainty with the JAYA controller was 73% of its nominal parameters. The simulation results were validated using an experimental testbed.

This research work is not published anywhere else.

The case study has been prepared for management students/business executives to understand electric vehicle (EV) business, business environment, industry competition and strategic planning and strategy implementation.

The size of the Indian passenger vehicle market was valued at US$32.70bn in 2021; it was projected to touch US$54.84bn by 2027 with a Compound Annual Growth Rate (CAGR) of more than 9% during the period 2022–2027. The passenger vehicle industry, a part of the overall automotive industry, was expected to grow at a rapid pace, as the Indian economy was rising at the fastest rate. However, the Government of India (GoI) had put a condition on the growth scenario by mandating that 100% of vehicles produced would be EVs by 2030. Tata Motors (TaMo), a domestic player in the market, had been facing a challenging competitive environment. Although it had been incurring losses, it had successfully ventured into the EV business. TaMo had taken advantage of the first mover by creating an electric mobility business vertical to enable the company to deliver on its aspiration of providing innovative and competitive e-mobility solutions. TaMo leadership had been putting efforts to scale up the electric mobility business, thus, contributing to GoI’s plan for electric mobility. Shailesh Chandra, president of electric mobility business, had a big task in hand. He had to scale up EV production and sales despite insufficient infrastructure for charging and shortages of electronic components for manufacturing.

The case study has been prepared for management students/business executives for strategic management class. It is recommended that the case study is distributed in advance so that the students can prepare well in advance for classroom discussions. Groups will be created to delve into details for a specific question. While one group will make their presentation, the other groups will question the solution provided and give suggestions.

Teaching notes are available for educators only.

CSS 11: Strategy.

Voltage source inverter-fed permanent magnet synchronous motors (VSI-PMSMs) are widely used in industrial actuation and mechatronic systems in water pumping stations, as well as in the traction of transportation systems (such as electric vehicles and electric trains or ships with electric propulsion). The dynamic model of VSI-PMSMs is multivariable and exhibits complicated nonlinear dynamics. The inverters’ currents, which are generated through a pulsewidth modulation process, are used to control the stator currents of the PMSM, which in turn control the rotational speed of this electric machine. So far, several nonlinear control schemes for VSI-PMSMs have been developed, having as primary objectives the precise tracking of setpoints by the system’s state variables and robustness to parametric changes or external perturbations. However, little has been done for the solution of the associated nonlinear optimal control problem. The purpose of this study/paper is to provide a novel nonlinear optimal control method for VSI-fed three-phase PMSMs.

The present article proposes a nonlinear optimal control approach for VSI-PMSMs. The nonlinear dynamic model of VSI-PMSMs undergoes approximate linearization around a temporary operating point, which is recomputed at each iteration of the control method. This temporary operating point is defined by the present value of the voltage source inverter-fed PMSM state vector and by the last sampled value of the motor’s control input vector. The linearization relies on Taylor series expansion and the calculation of the system’s Jacobian matrices. For the approximately linearized model of the voltage source inverter-fed PMSM, an H-infinity feedback controller is designed. For the computation of the controller’s feedback gains, an algebraic Riccati equation is iteratively solved at each time-step of the control method. The global asymptotic stability properties of the control method are proven through Lyapunov analysis. Finally, to implement state estimation-based control for this system, the H-infinity Kalman filter is proposed as a state observer. The proposed control method achieves fast and accurate tracking of the reference setpoints of the VSI-fed PMSM under moderate variations of the control inputs.

The proposed H-infinity controller provides the solution to the optimal control problem for the VSI-PMSM system under model uncertainty and external perturbations. Actually, this controller represents a min–max differential game taking place between the control inputs, which try to minimize a cost function that contains a quadratic term of the state vector’s tracking error, the model uncertainty, and exogenous disturbance terms, which try to maximize this cost function. To select the feedback gains of the stabilizing feedback controller, an algebraic Riccati equation is repetitively solved at each time-step of the control algorithm. To analyze the stability properties of the control scheme, the Lyapunov method is used. It is proven that the VSI-PMSM loop has the H-infinity tracking performance property, which signifies robustness against model uncertainty and disturbances. Moreover, under moderate conditions, the global asymptotic stability properties of this control scheme are proven. The proposed control method achieves fast tracking of reference setpoints by the VSI-PMSM state variables, while keeping also moderate the variations of the control inputs. The latter property indicates that energy consumption by the VSI-PMSM control loop can be minimized.

The proposed nonlinear optimal control method for the VSI-PMSM system exhibits several advantages: Comparing to global linearization-based control methods, such as Lie algebra-based control or differential flatness theory-based control, the nonlinear optimal control scheme avoids complicated state variable transformations (diffeomorphisms). Besides, its control inputs are applied directly to the initial nonlinear model of the VSI-PMSM system, and thus inverse transformations and the related singularity problems are also avoided. Compared with backstepping control, the nonlinear optimal control scheme does not require the state-space description of the controlled system to be found in the triangular (backstepping integral) form. Compared with sliding-mode control, there is no need to define in an often intuitive manner the sliding surfaces of the controlled system. Finally, compared with local model-based control, the article’s nonlinear optimal control method avoids linearization around multiple operating points and does not need the solution of multiple Riccati equations or LMIs. As a result of this, the nonlinear optimal control method requires less computational effort.

Voltage source inverter-fed permanent magnet synchronous motors (VSI-PMSMs) are widely used in industrial actuation and mechatronic systems in water pumping stations, as well as in the traction of transportation systems (such as electric vehicles and electric trains or ships with electric propulsion), The solution of the associated nonlinear control problem enables reliable and precise functioning of VSI-fd PMSMs. This in turn has a positive impact in all related industrial applications and in tasks of electric traction and propulsion where VSI-fed PMSMs are used. It is particularly important for electric transportation systems and for the wide use of electric vehicles as expected by green policies which aim at deploying electromotion and at achieving the Net Zero objective.

Unlike past approaches, in the new nonlinear optimal control method, linearization is performed around a temporary operating point, which is defined by the present value of the system’s state vector and by the last sampled value of the control input vector and not at points that belong to the desirable trajectory (setpoints). Besides, the Riccati equation, which is used for computing the feedback gains of the controller, is new, as is the global stability proof for this control method. Comparing with nonlinear model predictive control, which is a popular approach for treating the optimal control problem in industry, the new nonlinear optimal (H-infinity) control scheme is of proven global stability, and the convergence of its iterative search for the optimum does not depend on initial conditions and trials with multiple sets of controller parameters. It is also noteworthy that the nonlinear optimal control method is applicable to a wider class of dynamical systems than approaches based on the solution of state-dependent Riccati equations (SDRE). The SDRE approaches can be applied only to dynamical systems that can be transformed to the linear parameter varying form. Besides, the nonlinear optimal control method performs better than nonlinear optimal control schemes which use approximation of the solution of the Hamilton–Jacobi–Bellman equation by Galerkin series expansions.

The purpose of this paper is to verify results related to losses in the core of a brushless DC prototype motor, obtained using its computer FE models, by experimental tests on manufactured machines. The paper focuses on the comparison of losses in the core of a machine with a classical stator core made of an iron–silicon material (Fe–Si) and a new one made of a modern METGLAS material.

Computer models of the prototype motors were created using FEM. The designed machines were manufactured, and experimental tests were performed. To achieve high frequencies in rotating magnetic fields, motors with a stator to rotor pole ratio of 9/12 were built. Twin rotor approach was applied, as two identical rotors were built along the two geometrically identical stators made of different core materials.

Experimental studies have shown the superiority of the METGLAS material over the classical Fe–Si material. Material parameters were measured directly on the prepared cores as library data used in the simulation may be incorrect due to technological processes during core production, which was also verified. Problems related to twin rotor approach have been identified. Solution to the problem has been suggested. Necessity of 3D FEM modelling was identified.

The main source of originality is that METGLAS material used in the prototype machines was developed and manufactured by the authors themselves. Original approach to core parameter evaluation based on simplified methodology has been suggested. Another original part is a simplified methodology applied to loss measurement during no-load test.

Quantitative reliability analysis can effectively identify the time the driving system needs to be maintained. Then, the potential safety problems can be found, and some catastrophic failures can be effectively prevented. Therefore, this paper aims to evaluate the reliability of the switched reluctance generator (SRG) driving system.

In this paper, a method considering different thermal stresses and fault tolerance capacity is proposed to analyze the reliability of an SRG. A full-bridge power converter (FBPC) instead of the asymmetric half-bridge power converter (AHBPC) is adopted to drive the SRG system. First, the primary fault modes of the SRG system are introduced, and a fault criterion is proposed to determine whether the system fails. Second, the thermal circuit model of the converter is established to quickly and accurately obtain the junction temperature of the devices. At last, the Markov models of different levels are established to evaluate the reliability of the system.

The results show that the two-level Markov model is the most suitable when compared to the static model and the one-level Markov model.

The driving system of SRG will be more reliable after the reliability of the system is evaluated by the Markov model. At the same time, an FBPC is adopted to drive the SRG. The FBPCs have the advantages of fewer switching devices, higher integration and lower cost. The proposed driving strategy of the FBPC avoids the current reversal and the generation of dead zone time, which has the advantage of reliable operation. In addition, a precise thermal circuit model of the FBPC is proposed, and the junction temperature of each device can be obtained, respectively.

This paper aims to present an engineering computational method for fatigue life evaluation of welded structures on large-scale equipment under random vibration load.

Based on a case study of the traction transformers, virtual fatigue test (VFT) was proposed via numerical simulation approach. Static analysis was conducted to identify the risky zone and then dynamic response of the risky welds under random vibration load was calculated based on frequency-domain structural stress method (FDSSM) theory, life distribution and associated survivability at various locations of the structure were obtained. Structural modification was finally performed according to the evaluation results. Moreover, experimental test was carried out and compared with the virtual test result.

By applying the virtual test, fatigue life of the complex welded structures on large-scale equipment can be accurately and efficiently obtained considering dynamic effect under random vibration load. Meanwhile, risky welds can be directly determined and targeted modification scheme can be accordingly concluded. Validity of the VFT result was proved by comparing with the experimental test.

The proposed method can help obtain equivalent structural stress and fatigue life distribution of the welded structure at any position with various survivability and make quantitative evaluation on the life-extending effect of the structural modification. This method shows significant cost and efficiency advantages over experimental test during design stage of the large-scale structures in numerous manufacturing industries.

The rapid growth of emerging market firms (EMFs) has been a topic of interest for the past two decades, especially in China. However, few studies have discussed how and why EMFs can impel the upgrading of their capabilities to quickly win competitive advantages in the global market. In this context, the purpose of this paper is to unravel the implausible upgrading phenomenon from the perspective of technological proximity.

This paper adopts a single case study, specifically that of a leading Chinese e-bike firm, with a special focus on the dynamic nature of the capability upgrading process and underlying mechanisms.

The results show that taking advantage of technological proximity is an important way for EMFs to climb the ladder of capability upgrading. The stage-based process reveals how capability upgrading is achieved through elaborate actions related to technological proximity. Furthermore, this study finds three learning mechanisms behind the technological proximity, which enable firms to successfully upgrade to higher levels of capabilities. In particular, the trigger role played by contextual conditions in guiding firms' capability upgrading is highlighted and characterized.

This study enriches traditional capability upgrading literature from a technological proximity perspective, especially the traditional static upgrading research related to EMFs. The authors also contribute to the conceptualization of technological proximity. However, the research setting is China's e-bike industry; therefore, the study's generalizability to other emerging markets and industries may be limited.

The results show that it is important to recognize the value of the transfer and sharing of technology between proximal industries for local governments. Also, appropriate policies should be developed to break down the technology barriers between these industries. Moreover, rather than catching up with the superior technologies of multinational corporations in advanced countries, focusing on products with high technological proximity in local or regional areas may be more helpful for EMFs' upgrading.

This paper investigates the capability upgrading process and mechanisms in EMFs, particularly with respect to the role played by technological proximity.

Due to the structural layout, mining process, and working environment, curved chains such as horizontal and vertical bends inevitably exist in the armoured face conveyor (AFC). With the increasing power, conveying capacity, and distance of the AFC, the dynamic influence of these curved chains should be highly emphasized. This paper establishes a dynamic model of the AFC by multi-body system theory and finite segment method, in which the curved chains can be fully considered.

The scraper chains are firstly grouped into the straight, horizontal bend, vertical convex and concave bend sections. Each bend section running in a circle is simplified as an ideal arc. Through solving its differential equilibrium equation and using Newton's second law, its running resistance is derived. Then the grouped chains are discretized into finite control elements according to the Kelvin model, and the governing equation of each control element is established. The dynamic model of the AFC is obtained by assembling these equations, and the corresponding simulation model is developed by using MATLAB/Simulink.

Case studies with real scenarios are provided, and simulations are carried out. The results show that the running resistance contributed by the curved chains is larger than the traditional empirical value.

The work in this paper helps the dynamic performance design of AFC, with a deep understanding of the curved chains.

Most of the 3D printing machines do not comply with the requirements of on-site, large-scale multi-story building construction. This paper aims to propose the conceptualization of a tower crane (TC)-based 3D printing controlled by artificial intelligence (AI) as the first step towards a large 3D printing development for multi-story buildings. It also aims to overcome the most important limitation of additive manufacturing in the construction industry (the build volume) by exploiting the most important machine used in the field: TCs. It assesses the technology feasibility by investigating the accuracy reached in the printing process.

The research is composed of three main steps: firstly, the TC-based 3D printing concept is defined by proposing an aero-pendulum extruder stabilized by propellers to control the trajectory during the extrusion process; secondly, an AI-based system is defined to control both the crane and the extruder toolpath by exploiting deep reinforcement learning (DRL) control approach; thirdly the proposed framework is validated by simulating the dynamical system and analysing its performance.

The TC-based 3D printer can be effectively used for additive manufacturing in the construction industry. Both the TC and its extruder can be properly controlled by an AI-based control system. The paper shows the effectiveness of the aero-pendulum extruder controlled by AI demonstrated by simulations and validation. The AI-based control system allows for reaching an acceptable tolerance with respect to the ideal trajectory compared with the system tolerance without stabilization.

In related literature, scientific investigations concerning the use of crane systems for 3D printing and AI-based systems for control are completely missing. To the best of the authors’ knowledge, the proposed research demonstrates for the first time the effectiveness of this technology conceptualized and controlled with an intelligent DRL agent.

The results provide the first step towards the development of a new additive manufacturing system for multi-storey constructions exploiting the TC-based 3D printing. The demonstration of the conceptualization feasibility and the control system opens up new possibilities to activate experimental research for companies and research centres.