System Analytics
Agents: system analysts, business analysts, scientists, engineers;
Moves : requirements engineering, system design, prototype testing, production, erection, testing, commissioning;
RailTech System Intelligence
Prof. B. Williams and Dr. Andy Richardson are presenting system analytics for electrical and hybrid vehicles and railways technology. BEVs are the simplest type of EV using electrical power from a single source of battery to power one or more electric motors. A single electric motor is connected to the front axle through a simple gearbox; a series of four hub motors may be attached to each wheel. The battery has many cells combined into modules and the modules are grouped into packs through series and parallel connections. For example, 100 Li-ion series connected batteries with cell voltage of 3.6V can produce 360 V. The battery pack is the largest and most expensive component of the BEV; it is readily removable and swappable. Typically, EVs have higher initial costs, lower fuel costs, lower external costs, higher insurance costs, lower maintenance and repair costs. The cost of EV system depends on various types of elements such as size of key components (e.g. batteries, fuel cells, electric motors), desired performance, driving range, energy efficiency, cost of key materials for EV components (e.g. Li for batteries, platinum for fuel cells and carbon fiber for pressure vessels), life-cycle of key components, the impact of technological learning and economies of scale on manufacturing cost, energy use of EV, technology, design of the power train, drive cycle and weight; cost of energy (e.g. fuel production, distribution and delivery costs), insurance and maintenance cost.
There are various types of battery charging methods such as normal, induction, semi-fast and fast charging. Normal charging uses standard domestic socket, can be used anywhere but is limited in power. Semi-fast charging allows a higher charging power (up to 22 kW), suitable for most EVs. Fast charging needs a more expensive infrastructure. Inductive charging does not use plugs and cables and suitable for specific applications. The basic requirements of the technological innovation of EVs include availability of efficient electric energy storage devices or batteries and recharging infrastructure to transfer electric energy from the distribution grid to the battery.
EVs may also need intelligent communication protocol for vehicle identification and billing, charge cost optimization and grid load optimization. Typically, NCA (Li-Ni- Co), NCM (Li-Ni-Mn), LMO (Li-Mn spinel), LTO (Li-Titanate), Li ion Phosphate (LFP) technologies are used to make EV batteries. It is possible to do a comparative analysis of various types of batteries based on materials of anodes and cathodes, safety, performance,, cost, life-span, specific energy and specific power. The value chain associated with electrical vehicles has various processes such as component production, cell production, module production, pack assembly, vehicle integration, use, reuse and recycling.
Value chain analysis of EV batteries
Smart Batteries: Smart batteries are essential part of the dominant design of electrical and hybrid vehicles; Smart batteries should have higher energy density and tolerance to higher temperatures; should avoid the use of dangerous toxic materials, should be nonflammable and safe to use and should withstand higher voltage. Smart batteries are expected to be simple in design, cheaper and lighter in weight as compared to present batteries; won’t need liquid cooling; the batteries should be long lasting, fire-proof and should permit faster charging. Existing battery technology for EVs is very expensive and has limitations in terms of poor system performance at low temperature, impact of pressure, breakage due to mechanical stress and risks of dendrites.
EVs can be classified into non-hybrid vehicles (ICE) drive), hybrid electric vehicle (micro, mild, full, plug-in), extended range EV (EREV), BEV and fuel cell electric vehicle (FCEV). The hybrid solution obtains reduction of consumption and emissions; heat engines are operated more efficiently; electric power accumulators and electric motors allow energy recovery during braking and its use for traction purposes. In case of series hybrid vehicles, the electric motor supplies power to the wheels. In case of parallel hybrid vehicles, both the heat engine and the electric motor supply power to the wheels. In case of series-parallel hybrid vehicles, the heat engine can drive the wheels directly. It is an interesting agenda to do a multidimensional comparative analysis on various types of batteries (e.g. Li-Ni-Co- Al, Li-Ni-Mn-Co, Li-Mn, Li-Mn-P.,. Li-Ti) based on six dimensions – life span, cost, specific energy, specific power, dafety and performance.
Electrical Vehicle’s Battery Charging Mechanism
Let us analyze the battery charging mechanism of electrical and hybrid vehicles. The basic objective is to develop an efficient market mechanism or market interface where the trading agents i.e. the service consumers of electrical vehicles and the service providers of battery charging stations act rationally and negotiate a flexible and intelligent service contract on the replenishment of charged batteries based on approximate estimation of their preferences in EV charging scenario. The market mechanism is expected to maximize the utilities of the trading agents through efficient resource allocation subject to the constraints of time and cost and limited supply of electrical energy. Traditional auction mechanism may not be an interesting option in this business model.
Agents : Service consumer (B), Service provider (S);
Input: Demand plan of B, Supply plan of S;
System: Electrical / hybrid vehicles, batteries, battery charging stations,
Objectives: minimize mismatch between demand and supply plans of charged batteries;
Constraints: time, cost, technology;
Strategic moves : Select optimal resource allocation heuristics - FCFS (First Come First Served), Most Requests First (MRF), Longest Waits First (LWF), Selective resource allocation for emergency load (linear / proportional allocation);
Protocol: The agents settle single or multiple intelligent service contracts.: Collaborative planning, forecasting and replenishment (CPFR), Swing option, Push pull, Group buying;
Payment function: verify business intelligence of service contracts in terms of (pay per use, payment mode, payment terms);
Security intelligence: verify security intelligence in terms of rationality, fairness, correctness, transparency and accountability; B and S preserve privacy of SC contract as per revelation principle;
Output: Battery charging service contract.
Collaborative planning, forecasting and replenishment (CPFR) is a strategic tool for comprehensive value chain management. This is an initiative among all the stakeholders of the supply chain and service chain in order to improve their relationship through jointly managed planning, process and shared information. The ultimate goal is to improve the position of the battery charging service provider in the competitive market and the optimization of its own value chain in terms of optimal inventory, improved sales, higher precision of forecast, reduced cost and improved reaction time to customer demands. The interplay between trust and technology encourages the commitment of collaboration among the trading agents. Let us consider a specific scenario of multi-party negotiation in battery charging of electrical vehicles. Swing option is a specific type of supply contract in trading of stochastic demand of a resource such as charged battery for electrical / hybrid vehicles. It gives the owner of the swing option the right to change the required delivery of a resource through short time notice. It gives the owner of the swing option multiple exercise rights at many different time horizons with exercise amounts on a continuous scale. A typical swing option is defined by a set of characteristics and constraints. There are predefined exercise times ti, i 
[1,2,..,n], 1≤ t1≤t2…≤tn≤ T at which a fixed number of d0 units of a resource may be obtained. With a notice of specific short period, the owner of the option may use swing right to receive more (up-swing) or less (down-swing) than d0 at any of n moments. The scheme permits swing only at g out of possible n time moments where g ≤ n is swing number constraint. A freeze time constraint forbids swings within short interval of the moments. The local constraints up-swing [
] and down-swing limits [
] define how much the requested demand di at time ti may differ from d0. There are two global constraints which restrict the total requested volume D within the contract period by maximum total demand (
) and minimum total demand (
). The option holder must pay penalty determined by a function for violating local or global constraints. In this contract, the primary negotiation issue may be a discriminatory pricing plan which depends on the negotiation of a set of secondary issues such as up-swing limit, down-swing limit, maximum total demand, minimum total demand, penalty function and number of swings for a specific period.
Dr. Richardson is discussing various critical issues of railtech system. The system should be designed to satisfy multiple objectives subject to various constraints. The system should have clearly defined objectives, decision making procedures and quantitative measures of performance. The state of the system at a specific time is a set of properties of the system. RailTech system is a complex grouping of interlinked components; it can be decomposed into a set of interacting schema such as computing, networking, data, application and security schema. Each schema can be outlined as stated above. DAS is basically an information system. The basic building blocks of the computing schema are a set of algorithms which compute critical system parameters. The networking schema is the communication system. The data schema processes data collected by the sensors and various measuring instruments. The application schema defines the basic features of driver advice system. The complexity of the system should be analyzed in terms of number of interacting elements, number of relationships among the elements, number of objectives and number of ways the system interacts with internal and external environment.